Search Results (3,640)

This study reports the structural, optical, and photocatalytic properties of Nd-doped Al₂O₃ nanoparticles synthesized via a high-temperature solid-state reaction method. The impact of varying Nd concentrations (1%, 2%, and 3%) on the host lattice was investigated through X-ray diffraction (XRD), which confirmed the successful integration of Nd³⁺ ions and revealed a concentration-dependent lattice expansion. Diffuse Reflectance Spectroscopy (DRS) demonstrated characteristic 4f-4f transitions of Nd³⁺, while Tauc plot analysis indicated a systematic blue shift in the optical bandgap from 4.5 eV to 4.63 eV with an increasing dopant content. The photocatalytic efficiency was evaluated through the degradation of Basic Fuchsin (BF) dye under UV irradiation. The Al₂O₃:3% Nd sample exhibited superior performance, achieving an 83% degradation efficiency within 160 min, following pseudo-first-order Langmuir–Hinshelwood kinetics (k_obs = 0.02428 min⁻¹). Photoluminescence (PL) studies further corroborated the structural integrity and defect dynamics, showing a significant enhancement in NIR emission (880–920 nm) at higher doping levels without reaching the concentration-quenching threshold. These results suggest that Nd-doped Al₂O₃ nanoparticles are highly effective for environmental remediation and optoelectronic applications. Full article

Background: Nymphaea atrans exhibits a gradual flower color transition from nearly white to rose-red during anthesis, yet the molecular mechanisms of this phenomenon remain unclear. In the present study, transcriptomic and metabolomic analyses were performed to systematically investigate anthocyanin accumulation patterns and regulatory mechanisms during the color transition of N. atrans. Methods: Petals were collected at three flowering stages: day 1 (D1), day 3 (D3), and day 5 (D5). Targeted metabolomics was performed using UPLC-ESI-MS/MS to profile anthocyanin and other flavonoid metabolites. Transcriptome analysis was conducted via RNA-seq. Differentially accumulated metabolites (DAMs) and differentially expressed genes (DEGs) were identified, followed by functional enrichment and integration analysis. Results: The results revealed significant accumulation of seven anthocyanins, including cyanidin-3-O-arabinoside, cyanidin-3-O-glucoside, cyanidin-3-O-galactoside, cyanidin-3-O-(6″-O-acetyl)-glucoside, at stages D3 (day 3 after flowering, light pink petals) and D5 (day 5 after flowering, deep pink petals), accompanied by the upregulation of key enzyme-encoding genes, chalcone synthase, chalcone isomerase, flavanone 3-hydroxylase, di-hydroflavonol 4-reductase, and anthocyanidin synthase in the anthocyanin biosynthetic pathway. Genes involved in JA biosynthesis and key regulatory genes in the JA signaling pathway were significantly up-regulated, indicating that the JA signaling pathway may play an important regulatory role in the synthesis of anthocyanins in N. atrans. Conclusions: This study unravels the metabolic and molecular underpinnings of flower color transition in N. atrans, thereby establishing a theoretical basis for the targeted regulation of floral pigmentation and molecular breeding of ornamental water lilies. Full article

To enhance fleet replenishment efficiency and ensure navigational safety, this paper investigates the Underway Replenishment Routing Problem (URRP), focusing on the dynamic characteristics of receiving ships. Mathematical models for replenishment ship travel time and formation vessel speed adjustment are formulated, explicitly considering navigational state transitions and formation stability (risk control). Consequently, a dynamic route optimization model is constructed to provide intelligent decision support for fleet commanders. An intelligent optimization algorithm, the Hybrid Genetic Algorithm with Adaptive Variable Neighborhood Search (HGA-AVNS), is proposed to solve this model. Computational results demonstrate that the proposed approach outperforms the traditional empirical replenishment strategy, validating its effectiveness in enhancing maritime safety and operational efficiency. Extensive sensitivity analyses further reveal that under the strict premise of maintaining formation stability, appropriately reducing the cruise speed can offset the increase in overall speed over ground (SOG) induced by following ocean currents, thereby preventing systematic time loss. Additionally, fine-tuning the execution timing of sudden tactical turning based on the replenishment ship’s real-time operational status can further maximize overall replenishment efficiency without compromising navigational safety. Full article

Sorption thermal energy storage is pivotal for enhancing renewable energy utilization and supporting the transition to carbon neutrality. Its performance hinges on the formation and dynamic evolution of the reaction zone. However, the lack of in situ, spatially resolved measurement tools has hampered a mechanistic understanding and rational design. To address this, this study presents a method for characterizing the reaction zone dynamics through high-resolution intra-reactor temperature profiling. Applying this method to a zeolite 13X packed-bed reactor, we establish, for the first time, quantitative empirical correlations between operating parameters and these intrinsic reaction zone properties. A key finding is that the stable duration and output temperature are governed by the length, propagation velocity, and exothermic area of the reaction zone, coupled with the total sorption heat. Furthermore, the effects of the four critical operational parameters, including inlet air temperature, relative humidity, airflow rate, and packing thickness, on both the reaction zone characteristics and thermal output performances were systematically investigated. By integrating these mechanistic insights, we propose a hierarchical control strategy and actionable application guidelines to tailor the thermal output on demand. Full article

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