Search Results (3,636)

Composite specimens of normal concrete (NC) and ultra-high performance concrete (UHPC) in marine tidal zones are susceptible to coupled physico-chemical degradation under seawater wet–dry cycling; however, the microscopic damage-evolution mechanisms within the NC/overlay transition zone (OTZ)/UHPC three-phase region remain unclear. In this study, accelerated erosion was conducted using 10-fold concentrated artificial seawater under 0, 30, 60, and 90 wet–dry cycles. The X-ray computed tomography, mercury intrusion porosimetry, backscattered electron imaging coupled with energy dispersive X-ray spectroscopy and slant shear tests were employed to systematically investigate the macroscopic bonding performance and microscopic structural damage of NC-UHPC composites. The results show that the interfacial bond strength initially increases and then declines, exhibiting a 13.53% improvement after 30 wet–dry cycles and a sharp 41.55% decrease after 90 cycles compared with that after 60 cycles. The damage severity was the highest in NC, intermediate in OTZ, and lowest in UHPC. The gas-rich pore region within the OTZ provides a stress-buffering effect during the early stage of corrosion. After 90 wet–dry cycles, the total porosity increased by 0.14%, with external porosity increasing by 0.21% and internal porosity decreasing by 0.07%, indicating a pore-structure reconfiguration characterized by micropore coalescence and an increased proportion of macropores. These findings clarify the damage process associated with seawater erosion, pore expansion, and interfacial failure, providing theoretical support for the repair design and durability assessment of marine concrete structures. Full article

Given that the construction industry is a major source of energy consumption and carbon emissions, its green transition holds significant implications for both economic development and environmental sustainability. This study takes the digital economy as its point of departure and systematically examines its impact on the carbon emission intensity in the construction industry, as well as underlying transmission mechanisms. Based on theoretical analysis, this study employs fixed-effects and mediation-effects models for empirical testing. The study finds that the digital economy can significantly reduce the carbon emission intensity of the construction industry, a conclusion that remains robust after a series of robustness tests. Mechanism analysis shows that industrial structure optimization plays an important mediating role in the process through which the digital economy promotes the reduction of carbon emission intensity in the construction industry. Heterogeneity analysis indicates that the impact of the digital economy on the carbon intensity in the construction industry is greater in the central and western regions than in the eastern regions. However, this impact is relatively smaller in regions with high urbanization levels than in those with average urbanization levels. At the same time, the impact of the digital economy on the carbon intensity in the construction industry is greater in low-income regions than in high-income regions. Finally, the study proposes measures to reduce the carbon emission intensity of the construction industry. Full article

The environmental impacts from fossil fuel use have accelerated the global transition to sustainable energy sources. Hydrogen has become a promising alternative due to its high energy density and clean combustion. However, hydrogen production streams are frequently contaminated with methane, which needs efficient, durable, and cost-effective purification technologies such as pressure swing adsorption (PSA). The present study provides a comparative evaluation of biomass-derived activated carbons and a commercial activated carbon for hydrogen–methane separation. High-surface-area activated carbons were synthesized from sustainable pine and birch precursors via chemical activation using potassium hydroxide (KOH, impregnation ratio 3:1) at 800 °C. Their dynamic adsorption performance was systematically assessed in a fixed-bed setup under a PSA system operating at pressures of 25, 35, and 50 bar, using a of hydrogen–methane gas mixture, where methane feed concentrations ranging from 10 to 30 vol%. This work focuses on the behavior of the adsorbent material and does not constitute a complete PSA process evaluation. The biomass-derived activated carbons showed well-developed textural characteristics, with specific surface areas up to 1416 m² g⁻¹, which exceeded that of the commercial reference material (1023 m² g⁻¹). This improved pore structure was reflected in their adsorption behavior at an operating pressure of 50 bar; the birch-derived carbon achieved a methane uptake of 10.5 mol kg⁻¹, more than twice the capacity of 5.30 mol kg⁻¹ measured for the commercial adsorbent. Beyond initial adsorption capacity, the study emphasizes operational durability and reusability. Cyclic adsorption–desorption experiments, supported by Raman spectroscopy, revealed pronounced structural changes in the commercial activated carbon under repeated operational stress, as indicated by an increase in the I_D/I_G ratio from 1.08 to 1.24. In contrast, the biomass-derived activated carbons preserved their morphological integrity and adsorption efficiency over successive cycles. These findings demonstrate that pine- and birch-derived activated carbons are not only sustainable alternatives but also operationally stable adsorbents capable for hydrogen purification processes. Full article

The agricultural sector is undergoing a profound digital transformation driven by artificial intelligence, the Internet of Things, remote sensing, robotics, blockchain, and edge computing, which are being integrated into crop monitoring, irrigation management, disease detection, and supply chain transparency systems. This study employs systematic evidence mapping to characterize the applications of emerging digital technologies in sustainable agriculture; it delineates technological trajectories, areas of application, implementation gaps, and opportunities for improvement. Adhering to the PRISMA 2020 reporting protocol, 101 peer-reviewed articles indexed in Scopus and Web of Science (2020–2025) were identified, screened, and subjected to integrated thematic and bibliometric synthesis, using RStudio Version: 2026.01.1+403 and VOSviewer 1.6.20 for data mining on keywords and technological evolution patterns. Results show that deep learning and computer vision models achieved diagnostic accuracies of 90–99%, smart irrigation systems reduced water consumption by 10–30%, predictive yield models frequently reported R² values above 0.80, and greenhouse automation reduced energy consumption by approximately 20–30%. Blockchain-based architectures improved traceability and secure data transmission by 15–20%, while remote sensing integration enhanced spatial estimation accuracy up to R² = 0.92. The findings demonstrate a measurable transition toward data-driven, resource-efficient agricultural ecosystems supported by validated digital architectures. However, interoperability limitations, lack of standardized performance metrics, scalability challenges, and uneven geographical implementation—identified in nearly 40% of studies—highlight the need for harmonized evaluation frameworks, cross-platform integration standards, and long-term field validation to ensure sustainable and scalable digital transformation. Full article

The exploration of deep-sea microorganisms is transitioning from ex situ laboratory analysis to in situ real-time monitoring. While in situ technologies offer unprecedented access to microbial activities in their natural extreme habitats, they face a critical, yet often overlooked, bottleneck: the absence of a robust metrological framework. This lack of standardized calibration, traceability, and reference materials results in data that are often irreproducible, device-specific, and incomparable across studies, severely undermining scientific discovery and resource assessment. This review provides a systematic analysis of the current landscape of deep-sea microbial detection technologies, categorizing them by their operational principles and critically evaluating their performance, limitations, and metrological readiness. By synthesizing the technological challenges with the principles of metrology, we identify the fundamental gap between advanced sensing capabilities and the lack of in situ measurement standards. To bridge this gap, we propose an innovative “laboratory simulation–in situ detection–remote calibration” trinity calibration system. This framework establishes a complete metrological traceability chain tailored for extreme deep-sea conditions, aiming to transform isolated sensor data into globally comparable, scientifically robust, and industrially actionable information, thereby paving the way for precision deep-sea biology and governance. Full article

Emerging evidence indicates that non-coding RNAs (ncRNAs) play important regulatory roles in honeybee social behavior and development. However, the regulatory roles of ncRNAs in honeybees remain largely elusive. To systematically identify ncRNAs associated with queen-regulated ovary activation, we conducted whole-transcriptome sequencing on the heads of Apis mellifera workers from queenright and queenless colonies. Subsequent bioinformatics analyses were conducted to profile differentially expressed (DE) RNAs and construct potential regulatory networks. High-quality sequencing data provided a foundation for subsequent analyses. This transcriptome data yielded 3968 lncRNA transcripts, comprising 3146 known and 822 novel candidates, all of which exhibited typical structural features of lncRNAs. Comparative expression analyses revealed that 246 lncRNAs, 1439 mRNAs, and 10 miRNAs were differentially expressed. Comprehensive functional analyses indicated that the identified DElncRNAs potentially regulate sensory perception-related target mRNAs via cis-regulation, and coordinate metabolic and proteostatic reprogramming via trans-regulation to support the transition to reproductive activation in workers. Furthermore, a competing endogenous RNA network was constructed which integrated 74 DElncRNAs, 5 DEmiRNAs, and 36 DEmRNAs to predict their potential post-transcriptional interactions. Our findings highlight a comprehensive analysis of ncRNAs and mRNAs in worker heads, providing a foundation for functional validation of their roles in honeybee ovary development. Full article

Remote ischemic conditioning (RIC) is an endogenous strategy that mitigates cerebral injury in preclinical stroke models. However, its bench-to-bedside translation is frequently hindered by complex patient environments that induce RIC resistance and limit its neuroprotective efficacy. To bridge this translational gap, this review systematically examines the extrinsic pathophysiological and pharmacological barriers to RIC. We categorize RIC resistance into three mechanism-driven phenotypes. Impaired signal initiation (Type I) is often linked to diabetic sensorimotor polyneuropathy and the reactive oxygen species-scavenging effects of propofol. Signal transmission blockade (Type II) is associated with specific P2Y12 inhibitors and smoking-induced endothelial dysfunction. Furthermore, effector desensitization (Type III) involves target-organ unresponsiveness exacerbated by aging, chronic hyperglycemia, and postmenopausal estrogen depletion. To address these barriers, potential phenotype-specific optimization strategies are discussed. Ultimately, transitioning from generalized empirical protocols to mechanism-based precision strategies may help bypass RIC resistance in clinical settings and enhance stroke cerebroprotection. Full article

Liquidambar formosana Hance, a tree species in subtropical broad-leaved forests, exhibits a striking autumn leaf coloration. However, how drought stress during this period influences leaf color change remains poorly understood. In this study, two-year-old seedlings were subjected to four drought gradients. Leaf color parameters, pigment contents, cellular structure, photosynthetic physiology, and hydraulic properties were systematically measured throughout the leaf color transition period. The results show that, with increasing drought severity, leaf red-green coordinate a* increased significantly during early-to-middle stress (S1–S3), while lightness L* and yellow-blue coordinate b* increased at late stress (S4). Chlorophyll (Chl) content continuously decreased, anthocyanins (Ant) peaked at mid-stress, and carotenoids (Car) became enriched at late stress. Leaf cellular structure and hydraulic parameters declined, photosynthetic function was inhibited, and antioxidant enzyme activities showed an initial increase followed by a decrease. Correlation analysis and Random Forest models revealed that L* was strongly associated with superoxide dismutase (SOD) activity, carotenoid-to-chlorophyll (Car/Chl) ratio, and net photosynthetic rate (P_n); a* was closely linked to osmotic potential at full saturation (Ψ_sat), relative water content at the turgor loss point (RWCtlp), SOD activity, Car/Chl ratio, anthocyanin-to-chlorophyll (Ant/Chl) ratio, Ant content, transpiration rate (T_r), P_n, and main vein thickness (Mvt), while b* was primarily correlated with Ψ_sat, Car/Chl ratio, SOD activity, Ant/Chl ratio, and P_n. These statistical associations suggest multiple physiological processes are involved in leaf color change. Based on these findings, we propose a hypothetical sequence: drought initially disrupts leaf water status, leading to structural atrophy and hydraulic decline, followed by photosynthetic inhibition, activated antioxidant defense, and altered pigment accumulation, which are correlated with the sequential leaf color transition from green to red to yellow-orange in this species. Full article

This study systematizes the form generation process using machine learning-driven motion-tracking data and investigates the interrelationships between the characteristics of generated data and forms generated according to data-processing methods. Through the vision-based machine learning motion estimation (VideoPose3D) algorithm, 3D motion data are extracted from 2D video and categorized into point (joint), curve (bone), and boundary (range of motion) types. Furthermore, this study analyzes the form generation characteristics and limitations associated with each type of motion-tracking data derived from dynamic-to-dynamic physical activities with postural transitions. A data-processing methodology based on artistic practice from prior research is applied. The characteristics of generated data and the morphological characteristics of generated forms are then analyzed according to non-processed and processed methods. Results suggest a potential correlative tendency between the characteristics and generated forms of each type of motion data value information. A bidirectional complementary relationship exists between non-processed and processed motion-tracking data. The data-based form generation methodology demonstrates potential applicability in architectural design. This study expands design possibilities by supporting decisions early in the architectural design process and immediately generating diverse alternatives; it also proposes a standardized framework for a universal data-centric design process applicable to diverse data types, including motion data. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD), is the most common chronic liver disease in the world. The disease progresses from steatosis to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis, and hepatocellular carcinoma. The modern concept of “multiple parallel hits” interprets disease progression as the result of the synergistic action of lipotoxicity, oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, proinflammatory signals, and gut–liver axis dysfunction. Against the background of the limited translation of preclinical data from animal models due to interspecies differences, the importance of human-oriented in vitro platforms compatible with controlled design and high-throughput screening is increasing. The current review analyzes MASLD models based on the HepG2 cell line, systematizing steatosis induction protocols, evaluating the metabolic characteristics and limitations of this cell, and comparing 2D monocultures, 3D systems, and co-cultures. HepG2 has been shown to demonstrate a predictable steatogenic response to free fatty acids (FFAs) and is convenient for reproducing early stages of pathogenesis and primary pharmacological selection of compounds. At the same time, key limitations of the model are highlighted, namely tumor origin, glycolytic shift (Warburg effect), reduced β-oxidation, impaired very-low-density lipoprotein (VLDL) assembly and secretion, and sharply reduced cytochrome P450 (CYP450) activity, as well as limited reproducibility of fructose-induced de novo lipogenesis (DNL). Comparative analysis demonstrates an increase in physiological relevance with the transition from 2D to 3D and multicomponent co-cultures, accompanied by increased complexity and cost, but allowing for the modeling of inflammation and fibrogenesis. The review justifies approaches to selecting the appropriate platform based on the specific research task. Full article

C₁₃-Norisoprenoids are important contributors to the aroma of Riesling wine. Their quantification is analytically challenging due to their low concentrations, the lack of commercial standards and their pronounced sensitivity to analytical conditions, reflecting their chemical lability, as well as the dynamic nature of the wine matrix, leading to high reactivity and, consequently, remarkable structural diversity. Here, we developed an assay for the analysis of C₁₃-norisoprenoids in wine using headspace solid-phase microextraction coupled to gas chromatography–mass spectrometry (HS-SPME–GC-MS/MS). After evaluating different fiber materials, a statistical design of experiments (DoE) approach was employed to systematically optimize key HS-SPME parameters, including incubation, extraction and desorption conditions. Selected reaction monitoring (SRM) transitions were established for all targeted C₁₃-norisoprenoids, allowing the assay to provide relative quantification of more than 40 compounds using representative labeled and unlabeled standards to generate linear calibration curves. Following method validation, this approach was applied to a young German Riesling wine to investigate the effect of various acidic hydrolysis conditions on the norisoprenoid profile as well as on specific compounds. A central composite design (CCD) was used to systematically study the impact of pH, temperature, and hydrolysis time. Quantitative data were obtained for 22 C₁₃-norisoprenoids demonstrating that hydrolysis conditions strongly affected the norisoprenoid composition. pH and temperature showed a greater influence than reaction time. Response surface models (RSM) indicated that TDN, Vitispirane and TPB in particular are predominantly formed under strongly acidic and high-temperature conditions, whereas others such as Riesling acetal and actinidols are formed under milder conditions. The results indicate that hydrolysis conditions should be tailored to the specific norisoprenoid under investigation and the research question, particularly when simulating conditions of accelerated wine ageing for analytical purposes. Full article

The transition from acute kidney injury (AKI) to chronic kidney disease (CKD) represents a dynamic and multistage pathological process driven by maladaptive intercellular communication. Rather than resulting from isolated cellular injury, AKI-CKD progression unfolds through a spatially and temporally coordinated dysregulation of cellular networks. In the acute phase, damaged tubular epithelial cells act as instigators, releasing damage-associated molecular patterns (DAMPs) and activating a storm of inflammatory crosstalk among immune cells, endothelium, and fibroblasts. During the subacute repair phase, imbalance in macrophage polarization (M1 persistence/M2 dysfunction) and the emergence of senescent tubular cells with a senescence-associated secretory phenotype (SASP) together create a pro-fibrotic microenvironment. In the chronic phase, activated myofibroblasts—derived from multiple sources—establish self-sustaining feedback loops via autocrine signaling, mechanical memory from the stiffened extracellular matrix (ECM), and ongoing dialogue with immune and resident cells, ultimately leading to irreversible fibrosis. Current therapeutic strategies focused on single molecular targets often fail to disrupt this resilient network homeostasis. Therefore, we propose a paradigm shift toward spatiotemporally precise network-remodeling therapies, which require integrated use of liquid biopsy-based staging, smart nanocarriers for cell-specific delivery, and AI-powered multi-omics modeling. This review systematically delineates the evolving cell-to-cell communication networks across AKI-CKD continuum and highlights innovative strategies to intercept disease progression by targeting the pathophysiology of cellular crosstalk. Full article

Land cover (LC) change is reshaping terrestrial ecosystems and profoundly impacting sustainable development in Africa, yet the long-term, continental-scale spatiotemporal dynamics of these shifts remain obscured. To address the above issue, this study systematically explores the spatiotemporal dynamics of LC across Africa from 1985 to 2022 by leveraging the fine-resolution remote-sensing-derived GLC_FCS30D LC dataset within a stratified Intensity Analysis framework. To decompose landscape changes into interval, category, and transition levels across five climatic sub-regions of Africa, we systematically evaluate the temporal consistency of land systems. This hierarchical approach disentangles systematic transition pathways from random fluctuations, thereby revealing the distinct regional regimes governing continental transformation of LC. Our results ultimately show a strong LC change acceleration in Africa after 2010, mainly in Southern, Eastern, and Western Africa, which together made up 80 to 90% of the continent’s LC dynamics. During the whole study period, shrubland and grassland had the highest gross turnover due to their high bidirectional volatility. Intensity-wise, forest remained inactive even though it was a persistent net loser to crop in East Africa (2010–2020), to shrub in Southern Africa (1990–2022), and to wetland in West Africa during the post-2000 intervals. Wetland had a major change in dynamics from historical growth during 1985–1990 to systematic decline in 2015–2022. Cropland increased by systematically targeting shrubland and grassland, mainly in East Africa. Additionally, the Sahel contributed 40% of continental grassland to bare area transitions, despite some recovery of grassland in the region. These findings show that aggregate net-change metrics obscure the volatility in African LC; therefore, distinct regional regimes such as agricultural expansion and forest degradation necessitate spatially differentiated management strategies. Full article

The Spur-thighed tortoise (Testudo graeca) is a long-lived terrestrial reptile listed as ‘Vulnerable’ on the IUCN Red List and protected under CITES Appendix II. As an ecosystem engineer, it plays a vital role in Mediterranean landscapes, yet it frequently faces anthropogenic pressures in urban environments. This study provides an ecological and ethological assessment of a captive T. graeca population (n = 42) in the historical Münire Madrasa Handicrafts Bazaar in Kastamonu, Türkiye. The methodology integrated spatial carrying capacity modeling (Boullon model), systematic ethogram-based observations (120 h), and ethnozoological surveys (n = 200). Spatial analysis revealed that the population exceeds the corrected Real Carrying Capacity (RCC ≈ 10) by four times (Overcapacity Index: 4.2) within the 70 m² area. Ethological findings documented chronic stress, with stereotypic pacing (H1) occupying 32% of the time budget, alongside a significant loss of anti-predator mechanisms due to anthropogenic habituation (İ1). While stakeholders (100%, 95% CI: 98.1–100%) perceive the tortoises as cultural symbols of abundance, the biological reality indicates severe welfare risks, including potential metabolic bone disease from a monotonous anthropogenic diet and a disrupted Ca:P ratio. The site is categorized as a ‘High-Constraint Interaction Zone’. We propose a management transition toward a monitored ‘Urban Wildlife Education Station’ to align local cultural values with international animal welfare and conservation standards. Full article

Urban socio-economic resilience to climate change has emerged as a central research theme as cities increasingly confront interconnected environmental, economic, and social risks. Despite the rapidly expanding body of literature, the conceptual boundaries, thematic evolution, and analytical priorities of this field remain fragmented across disciplines, and no prior study has systematically mapped the socio-economic dimension of urban resilience through a combined bibliometric and thematic analysis over a multi-decadal horizon. This study addresses that gap by providing a systematic review of global research on urban socio-economic resilience to climate change, integrating bibliometric and thematic analyses of peer-reviewed publications from 1990 to 2025. Following the PRISMA 2020 guidelines, records were retrieved from the Web of Science Core Collection and subjected to a multi-stage screening procedure that combined automated relevance scoring with mandatory manual validation of the socio-economic dimension, resulting in a final dataset of 5076 publications. The analysis examines conceptual interpretations of socio-economic resilience, dominant climate hazards affecting urban systems, methodological approaches and assessment indicators, adaptation strategies and governance responses, and emerging research gaps. The results reveal a marked acceleration of scientific output after 2015, driven by the Paris Agreement and the IPCC Special Report on Global Warming of 1.5 °C (2018). The bibliometric network analyses identify adaptation, vulnerability, flooding, and sustainability transitions as the core thematic clusters. The findings trace a paradigmatic trajectory from equilibrist recovery frameworks toward transformative, socio-economically grounded resilience models and reveal persistent gaps in the operationalization of governance, equity measurement, and geographic representation. By synthesizing three-and-a-half decades of scholarship, this review clarifies the intellectual structure of the field and proposes four specific post-2026 research pathways that emphasize longitudinal cross-city comparisons, mixed-methods assessments, sector-specific compound hazard analyses, and governance mechanism studies. Full article