Search Results (410,586)

Deep coalbed methane (CBM) reservoirs are characterized by high hydrocarbon content and are considered an important strategic resource. Due to their inherently low permeability and porosity, horizontal well drilling is commonly employed to enhance production, with the length of the horizontal section playing a critical role in determining CBM output. However, during extended horizontal drilling, wellbore instability frequently occurs as a result of drilling fluid invasion into the coal formation, posing significant safety challenges. This instability is primarily caused by the physical intrusion of drilling fluids and their interactions with the coal seam, which alter the mechanical integrity of the formation. To address these challenges, interpenetrating and semi-interpenetrating network (IPN/s-IPN) hydrogels have gained attention due to their superior physicochemical properties. This material offers enhanced sealing and support performance across fracture widths ranging from micrometers to millimeters, making it especially suited for plugging applications in deep CBM reservoirs. A self-degradable interpenetrating double-network hydrogel particle plugging agent (SSG) was developed in this study, using polyacrylamide (PAM) as the primary network and an ionic polymer as the secondary network. The SSG demonstrated excellent thermal stability, remaining intact for at least 40 h in simulated formation water at 120 °C with a degradation rate as high as 90.8%, thereby minimizing potential damage to the reservoir. After thermal aging at 120 °C, the SSG maintained strong plugging performance and favorable viscoelastic properties. A drilling fluid containing 2% SSG achieved an invasion depth of only 2.85 cm in an 80–100 mesh sand bed. The linear viscoelastic region (LVR) ranged from 0.1% to 0.98%, and the elastic modulus reached 2100 Pa, indicating robust mechanical support and deformation resistance. Full article

Objectives: The aim of this study was to evaluate the impact of four working heights on lumbar biomechanics during wall construction tasks, focusing on work-related musculoskeletal disorders (WMSDs). Methods: Fifteen young male participants performed simulated mortar-spreading and bricklaying tasks while actual body movements were recorded using Inertial Measurement Unit (IMU) sensors. Muscle activities of the lumbar erector spinae (ES), quadratus lumborum (QL), multifidus (MF), gluteus maximus (GM), and iliopsoas (IL) were estimated using a 3D musculoskeletal (MSK) model and measured via surface electromyography (sEMG). The analysis of variance (ANOVA) test was conducted to identify the significant differences in muscle activities across four working heights (i.e., foot, knee, waist, and shoulder). Results: Findings showed that working at foot-level height resulted in the highest muscle activity (7.6% to 40.6% increase), particularly in the ES and QL muscles, indicating an increased risk of WMSDs. The activities of the ES, MF, and GM muscles were statistically significant across both tasks and all working heights (p < 0.01). Conclusions: Both MSK and sEMG analyses indicated significantly lower muscle activities at knee and waist heights, suggesting these as the best working positions (47 cm to 107 cm) for minimizing the risk of WMSDs. Conversely, working at foot and shoulder heights was identified as a significant risk factor for WMSDs. Additionally, the similar trends observed between MSK simulations and sEMG data suggest that MSK modeling can effectively substitute for sEMG in future studies. These findings provide valuable insights into ergonomic work positioning to reduce WMSD risks among wall construction workers. Full article

Numerous studies have demonstrated that in residential areas of Western cities, both luxury and legacy effects significantly shape tree species diversity dynamics. However, the specific mechanisms driving these diversity patterns in China, where urbanization has progressed at an unprecedented pace, remain poorly understood. In this study we selected 20 residential settlements and 7 key socio-economic properties to investigate the change trend of tree diversity (2006–2021) and its socio-economic driving factors in Beijing. Our results demonstrate significant increases in total, native, and exotic tree species richness between 2006 and 2021 (p < 0.05), with average increases of 36%, 26%, and 55%, respectively. Total and exotic tree Shannon-Wiener indices, as well as exotic tree Simpson’s index, were also significantly higher in 2021 (p < 0.05). Housing prices was the dominant driver shaping total and exotic tree diversity, showing significant positive correlations with both metrics. In contrast, native tree diversity exhibited a strong positive association with neighborhood age. Our findings highlight two dominant mechanisms: legacy effect, where older neighborhoods preserve native diversity through historical planting practices, and luxury effect, where affluent communities drive exotic species proliferation through ornamental landscaping initiatives. These findings elucidate the dual dynamics of legacy conservation and luxury-driven cultivation in urban forest development, revealing how historical contingencies and contemporary socioeconomic forces jointly shape tree diversity patterns in urban ecosystems. Full article

This paper presents the multi-triangular ring and self-routing protocol (MTRSRP), which is a new decentralized strategy designed to boost throughput and network efficiency in multiring scatternets. MTRSRP comprises two primary phases: leader election and scatternet formation, which collaborate to establish an effective multi-triangular ring topology. In the leader election phase, nodes exchange broadcast messages to gather neighbor information and elect coordinators through a competitive process. The scatternet formation phase determines the optimal number of rings based on the coordinator’s collected node information and predefined rules. The master nodes then send unicast connection requests to establish piconets within the scatternet, following a predefined role table. Intra- and inter-bridge nodes were activated to interconnect the piconets, creating a cohesive multi-triangular ring scatternet. Additionally, MTRSRP incorporates a self-routing addressing scheme within the triangular ring architecture, optimizing packet transmission paths and reducing overhead by utilizing master/slave relationships established during scatternet formation. Simulation results indicate that MTRSRP with dual-bridge connectivity outperforms the cluster-based on-demand routing protocol and Bluetooth low-energy mesh schemes in key network transmission performance metrics such as the transmission rate, packet delay, and delivery ratio. In summary, MTRSRP significantly enhances throughput, optimizes routing paths, and improves network efficiency in multi-ring scatternets through its multi-triangular ring topology and self-routing capabilities. Full article

Green innovation is a critical driver of sustainable development, yet it often faces efficiency challenges in rapidly industrializing economies. This study investigates the effect of China’s Circular Economy Demonstration Policy (CEDP) on urban green innovation efficiency (GIE) using city-level panel data from 2010 to 2021. Employing a difference-in-differences (DID) approach, we find that CEDP significantly enhances GIE, with the policy effect becoming statistically significant after a three-year lag and accumulating over time. Robustness tests, including placebo analyses, alternative dependent variables, and propensity score matching, confirm the validity of the results. Mechanism analysis reveals that the policy improves green innovation primarily by reducing capital distortion, promoting market integration, and enhancing resource allocation efficiency. Further heterogeneity analyses show that the positive effects are stronger in central cities, capital cities, and eastern regions, reflecting the role of local economic and institutional conditions. The study concludes with policy implications emphasizing regionally tailored implementation, capacity building, and long-term commitment to maximize green innovation outcomes. Full article

Cyanobacteria are a prolific source of bioactive metabolites with expanding applications in sustainable agriculture and biotechnology. This work explores, for the first time in thermotolerant Colombian isolates, the impact of light spectrum, photoperiod, and irradiance on the co-production of exopolysaccharides (EPS) and indole-3-acetic acid (IAA). Six strains from hot-spring environments were screened under varying blue:red (B:R) LED ratios and full-spectrum illumination. Hapalosiphon sp. UFPS_002 outperformed all others, reaching ~290 mg L⁻¹ EPS and 28 µg mL⁻¹ IAA in the initial screen. Response-surface methodology was then used to optimize light intensity and photoperiod. EPS peaked at 281.4 mg L⁻¹ under a B:R ratio of 1:5 LED, 85 µmol m⁻² s⁻¹, and a 14.5 h light cycle, whereas IAA was maximized at 34.4 µg mL⁻¹ under cool-white LEDs at a similar irradiance. The quadratic models exhibited excellent predictive power (R² > 0.98) and a non-significant lack of fit, confirming the light regime as the dominant driver of metabolite yield. These results demonstrate that precise photonic tuning can selectively steer carbon flux toward either EPS or IAA, providing an energy-efficient strategy to upscale thermotolerant cyanobacteria for climate-resilient biofertilizers, bioplastics precursors, and other high-value bioproducts. Full article

Art therapy serves as a crucial intervention modality for children with autism spectrum disorder (ASD), demonstrating unique value in emotional expression, sensory integration, and social communication. However, current practice presents critical challenges, including the disconnect between design expertise and clinical needs, unclear mechanisms of environmental factors’ impact on therapeutic outcomes, and insufficient evidence-based support for technology integration. Purpose: This study aimed to construct an evidence-based theoretical framework for art therapy environment design for children with autism, clarifying the relationship between environmental design elements and therapeutic effectiveness. Methodology: Based on the Web of Science database, this study employed a dual-track approach comprising bibliometric analysis and micro-qualitative content analysis to systematically examine the knowledge structure and developmental trends. Research hotspots were identified through keyword co-occurrence network analysis using CiteSpace, while 24 representative design cases were analyzed to gain insights into design concepts, emerging technologies, and implementation principles. Key Findings: Through keyword network visualization analysis, this study identified ten primary research clusters that were systematically categorized into four core design elements: sensory feedback design, behavioral guidance design, emotional resonance design, and therapeutic support design. A responsive therapeutic environment conceptual framework was proposed, encompassing four interconnected components based on the ABC model from positive psychology: emotional, sensory, environmental, and behavioral dimensions. Evidence-based design principles were established emphasizing child-centeredness, the promotion of multisensory expression, the achievement of dynamic feedback, and appropriate technology integration. Research Contribution: This research establishes theoretical connections between environmental design elements and art therapy effectiveness, providing a systematic design guidance framework for interdisciplinary teams, including environmental designers, clinical practitioners, technology developers, and healthcare administrators. The framework positions technology as a therapeutic mediator rather than a driver, ensuring technological integration supports rather than interferes with children’s natural creative impulses. This contributes to creating more effective environmental spaces for art therapy activities for children with autism while aligning with SDG3 goals for promoting mental health and reducing inequalities in therapeutic access. Full article

This paper introduces a robust and imperceptible video watermarking framework designed for blind extraction in dynamic video environments. The proposed method operates in the spatial domain and combines multiscale perceptual analysis, adaptive Just Noticeable Difference (JND)-based quantization, and temporal redundancy via multiframe embedding. Watermark bits are embedded selectively in blocks with high perceptual masking using a QIM strategy, and the corresponding DCT coefficients are estimated directly from the spatial domain to reduce complexity. To enhance resilience, each bit is redundantly inserted across multiple keyframes selected based on scene transitions. Extensive simulations over 21 benchmark videos (CIF, 4CIF, HD) validate that the method achieves superior performance in robustness and perceptual quality, with an average Bit Error Rate (BER) of 1.03%, PSNR of 50.1 dB, SSIM of 0.996, and VMAF of 97.3 under compression, noise, cropping, and temporal desynchronization. The system outperforms several recent state-of-the-art techniques in both quality and speed, requiring no access to the original video during extraction. These results confirm the method’s viability for practical applications such as copyright protection and secure video streaming. Full article

Cyber threat intelligence summarization plays a critical role in enhancing threat awareness and operational response in cybersecurity. However, existing summarization models often fail to capture essential threat elements due to the unstructured nature of cyber threat intelligence documents and the lack of domain-specific knowledge. This paper presents a knowledge-guided cyber threat intelligence summarization framework via term-oriented input construction, designed to improve summary fidelity, semantic relevance, and model robustness. The proposed approach consists of two key components: a hybrid term construction pipeline that combines unsupervised keyword extraction and supervised term generation with rule-based refinement, and a knowledge-injected input construction paradigm that explicitly incorporates structured terms into the model input. This strategy enhances the model’s understanding of critical threat semantics without altering its architecture. Extensive experiments conducted on cyber threat intelligence summarization benchmarks under both zero-shot and supervised settings demonstrate that the proposed method consistently improves summarization performance across different models, offering strong generalization and deployment flexibility. Full article

Discovering, analyzing, and finding a key to understanding the physiological and biochemical responses that Vitis vinifera L. undertakes against drought stress is of fundamental importance for this profitable crop. Today’s considerable climatic fluctuations force researchers and farmers to focus on this issue with solutions inclined to respect the ecosystem. In this academic work, we focused on describing the drought stress consequences on several parameters of secondary metabolites on Vitis vinifera leaves (quercetins, kaempferol, resveratrol, proline, and xanthophylls) and on some ecophysiological characteristics (e.g., water potential, stomatal conductance, and leaf temperature) to compare the answers that diverse agronomic management techniques (i.e., irrigation with and without zeolite, pure zeolite and no application) could instaurate in the metabolic pathway of this important crop with the aim to find convincing and thought-provoking responses to use this captivating and versatile mineral, the zeolite known as the “magic rock”. Stressed grapevines reached 56.80 mmol/m²s gs at veraison and a more negative stem Ψ (+10.63%) compared to plants with zeolite. Resveratrol, in the hottest season, fluctuated from 0.18–0.19 mg/g in zeolite treatments to 0.37 mg/g in stressed vines. Quercetins were inclined to accumulate in response to drought stress too. In fact, we recorded a peak of quercetin (3-O-glucoside + 3-O-glucuronide) of 11.20 mg/g at veraison in stressed plants. It is interesting to note how the pool of metabolites was often unchanged for plants treated with zeolite and for plants treated with water only, thus elevating this mineral to a “stress reliever”. Full article

This thesis pioneers the development of q-Rung Neutrosophic Fuzzy Rough Sets (q-RNFRSs), establishing the first theoretical framework that integrates q-Rung Neutrosophic Sets with rough approximations to break through the conventional ${\mu }^q+{\eta }^q+{\nu }^q\le 1$ constraint of existing fuzzy–rough hybrids, achieving unprecedented capability in extreme uncertainty representation through our generalized model (${\mathcal{T}}^q+{\mathcal{I}}^q+{\mathcal{F}}^q\le 3$). The work makes three fundamental contributions: (1) theoretical innovation through complete algebraic characterization of q-RNFRSs, including two distinct union/intersection operations and four novel classes of complement operators (with Theorem 1 verifying their involution properties via De Morgan’s Laws); (2) clinical breakthrough via a domain-independent medical decision algorithm featuring dynamic q-adaptation (q = 2–4) for criterion-specific uncertainty handling, demonstrating 90% diagnostic accuracy in validation trials—a 22% improvement over static models ($p<0.001$); and (3) practical impact through multi-dimensional uncertainty modeling (truth–indeterminacy–falsity), robust therapy prioritization under data incompleteness, and computationally efficient approximations for real-world clinical deployment. Full article

Background/Objectives: The integration of artificial intelligence (AI) in medical imaging is rapidly advancing, yet its application in gynecologic use remains limited. This proof-of-concept study presents the development and validation of a convolutional neural network (CNN) designed to automatically detect and classify endometrial polyps. Methods: A multicenter dataset (n = 3) comprising 65 hysteroscopies was used, yielding 33,239 frames and 37,512 annotated objects. Still frames were extracted from full-length videos and annotated for the presence of histologically confirmed polyps. A YOLOv1-based object detection model was used with a 70–20–10 split for training, validation, and testing. Primary performance metrics included recall, precision, and mean average precision at an intersection over union (IoU) ≥ 0.50 (mAP50). Frame-level classification metrics were also computed to evaluate clinical applicability. Results: The model achieved a recall of 0.96 and precision of 0.95 for polyp detection, with a mAP50 of 0.98. At the frame level, mean recall was 0.75, precision 0.98, and F1 score 0.82, confirming high detection and classification performance. Conclusions: This study presents a CNN trained on multicenter, real-world data that detects and classifies polyps simultaneously with high diagnostic and localization performance, supported by explainable AI features that enhance its clinical integration and technological readiness. Although currently limited to binary classification, this study demonstrates the feasibility and potential of AI to reduce diagnostic subjectivity and inter-observer variability in hysteroscopy. Future work will focus on expanding the model’s capabilities to classify a broader range of endometrial pathologies, enhance generalizability, and validate performance in real-time clinical settings. Full article

Polyvinyl chloride (PVC) is commonly employed as mulch in agriculture to boost crop yields. However, its toxicity is often overlooked. Due to its chemical stability, resistance to degradation, and the inadequacy of the recycling system, PVC tends to persist in farm environments, where it can decompose into microplastics (MPs) or nanoplastics (NPs). The radish (Raphanus sativus L.) was chosen as the model plant for this study to evaluate the underlying toxic mechanisms of PVC NPs on seedling growth through the integration of multi-omics approaches with oxidative stress evaluations. The results indicated that, compared with the control group, the shoot lengths in the 5 mg/L and 150 mg/L treatment groups decreased by 33.7% and 18.0%, respectively, and the root lengths decreased by 28.3% and 11.3%, respectively. However, there was no observable effect on seed germination rates. Except for the peroxidase (POD) activity in the 150 mg/L group, all antioxidant enzyme activities and malondialdehyde (MDA) levels were higher in the treated root tips than in the control group. Both transcriptome and metabolomic analysis profiles showed 2075 and 4635 differentially expressed genes (DEGs) in the high- and low-concentration groups, respectively, and 1961 metabolites under each treatment. PVC NPs predominantly influenced seedling growth by interfering with plant hormone signaling pathways and phenylpropanoid production. Notably, the reported toxicity was more evident at lower concentrations. This can be accounted for by the plant’s “growth-defense trade-off” strategy and the manner in which nanoparticles aggregate. By clarifying how PVC NPs coordinately regulate plant stress responses via hormone signaling and phenylpropanoid biosynthesis pathways, this research offers a scientific basis for assessing environmental concerns related to nanoplastics in agricultural systems. Full article

The penetration rate of variable energy sources in the current power grid is increasing, with the aim being to expand the use of these energy sources and to replace the traditional black start power supply. This study investigates the black start of a photovoltaic storage joint system based on the system’s short-circuit ratio threshold. Firstly, the principles and control modes of the photovoltaic (PV) system, energy storage system (ESS), and high-voltage direct current (DC) transmission system are studied separately to build an overall model; secondly, computational determinations of the short-circuit ratio under different scenarios are introduced to analyze the strength of the system, and the virtual inertia and virtual damping of the PV system are configured based on this; finally, the change trend of the storage system’s state of charge (SOC) is computed and observed, and the limits of what the system can support in each stage are determined. An electromagnetic transient simulation model of a black start system is constructed in PSCAD/EMTDC, and according to the proposed recovery strategy, the system frequency is maintained in the range of 49.4~50.6 Hz during the entire black start process; the fluctuation in maximum frequency after the recovery of the DC transmission system is no more than 0.1%; and the fluctuation in photovoltaic power at each stage is less than 3%. In addition, all the key indexes meet the requirements for black start technology, which verifies the validity of the strategy and provides theoretical support and a practical reference for the black start of a grid with variable energy sources. Full article

Virginia’s coastal location and abundant marine resources make its seafood industry a vital contributor to the state’s economy, supporting both local communities and tourism. This study applied input–output models and updates the economic contributions of the Virginia seafood industry using 2023 data, building on models developed for 2019 that capture both direct effects and broader economic ripple effects. In 2023, the industry generated USD 1.27 billion in total economic output and supported over 6500 jobs—including watermen, aquaculture farmers, processors, and distributors—resulting in USD 238.3 million in labor income. Contributions to state GDP totaled USD 976.7 million, and tax revenues exceeded USD 390.4 million. The study also evaluates the economic role of Virginia seafood products sold in retail stores and restaurants, based on secondary data sources. In 2023, these sectors generated USD 458 million in economic output, supported more than 3600 jobs, produced USD 136.7 million in labor income, and USD 280.8 million in value-added. Combined tax contributions surpassed USD 74 million. Importantly, the analysis results for the Virginia seafood products from retail and restaurant should not be summed to the seafood industry totals to avoid double-counting, as seafood products move as output from one sector as an input to another. These results provide evidence-based insights to guide decision-making, inform stakeholders, and support continued investment in Virginia’s seafood supply chain and related economic activities. Full article