Search Results (48)

This work presents the design, development, and proof-of-concept validation of a smart greenhouse for romaine lettuce (Lactuca sativa var. longifolia) that integrates Internet of Things (IoT) sensing/actuation with an image-based crop state assessment pipeline. The proposed pipeline combines a lightweight AI image classifier with fractal texture descriptors (box-counting fractal dimension) to support the non-destructive monitoring of leaf condition and growth stage. The system also implements resilience-oriented resource strategies, including rainwater harvesting, graywater reuse, and a hybrid power supply (photovoltaic + grid backup). Water and energy indicators are reported as estimated values derived from the prototype operating profile and literature-based baseline values (i.e., contextual comparisons rather than a contemporaneous controlled trial). Using an expanded dataset (n = 1500 images) and an independent held-out test subset (n = 350), the image classifier achieved 97.1% accuracy, with detailed precision/recall/F1 metrics reported in the Results. Overall, the proposed architecture and evaluation workflow provide an accessible and reproducible pathway toward sustainable, low-cost smart greenhouses in resource-constrained settings. Full article

Resistivity is a key parameter in shale reservoir characterization. Diverse micro-pore types and complex conduction mechanisms in shale result in poor accuracy when applying existed conductivity models. Establishing a high-precision conductivity response model requires comprehensive consideration of the pore structure and clay-bound water conduction. The primary novelty of this work lies in replacing macroscopic empirical fitting parameters with a mechanistic, multi-dimensional fractal framework. We develop a novel conductivity response characterization model that explicitly couples multi-dimensional fractal pore structure theory with clay-bound water conduction. Experimental data verification demonstrates the new model’s superior characterization accuracy. Results indicate three distinct zones in the shale conductivity-pore water conductivity relationship: a nonlinear zone, a transition zone, and a linear zone. A higher cation exchange rate on clay surfaces leads to an increase in the nonlinear characteristics of the conductivity for both the shale and the pore water in low-salinity regions. An increase in the values of the conduction path fractal dimension, pore morphology fractal dimension, and pore fractal dimension all contribute to reduced shale conductivity. While sharing clay-induced conductivity terms with conventional dual-water and shale volume models, the new model offers advantages in operational simplicity and parameter accessibility. This research provides a physically rigorous and highly accessible approach for conductivity-based reservoir parameter calculation, offering new technical perspectives for complex shale oil/gas evaluation. Full article

Railways constitute a core component of China’s national comprehensive transportation network, and their spatial organization and temporal accessibility jointly shape transport integration and system efficiency. Identifying their evolution from the dual perspectives of spatial expansion and time compression is therefore of both theoretical and practical significance. Drawing on fractal theory, this study examines the structural characteristics, evolutionary trends, and driving factors of railway networks in China’s five major urban systems from 2014 to 2024 from a “space–time” dual perspective. The results show that railway networks exhibit a staged pattern of “spatial filling preceding temporal correlation”, with a lag of approximately 1–8 years—about 1 year in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), 5 years in the Middle Yangtze River (MYR) region and Beijing–Tianjin–Hebei (BTH), and up to 8 years in the Chengdu–Chongqing (CC) region. In addition, clear regional differences are observed: the Yangtze River Delta (YRD) is polycentric, with the greatest potential, projected to continue rapid spatial growth until 2027 and to remain in a fast-growth phase of temporal correlation; GBA is highly coordinated; BTH is developed but characterized by dual-core agglomeration; CC grows rapidly with lagging functionality; and MYR is corridor-dependent with limited potential. These findings indicate that network functionality does not emerge synchronously with infrastructure expansion, but depends on subsequent improvements in operational organization and service capacity. Compared with single-scale-based indicators, the “spatial distribution–temporal correlation” framework more effectively captures network performance and provides quantitative support for transport optimization and coordinated regional development. Full article

Postural sway derived from center-of-pressure (CoP) trajectories is widely used to assess balance and fall risk in older adults, but conventional linear metrics mainly quantify sway magnitude and may overlook temporal organization. Guided by the loss-of-complexity hypothesis, we re-examined associations between fall history and linear and non-linear CoP metrics in an open-access dataset. Quiet-standing trials under eyes-open and eyes-closed conditions were analyzed in adults ≥60 years (fallers n = 19; non-fallers n = 57). To reduce confounding, propensity score matching was performed using age, sex, body mass index, activities of daily living level, illness status, number of medications, disability status, and orthosis/prosthesis use. Linear and non-linear indices, including recurrence quantification analysis, detrended fluctuation analysis, fractal dimension, multiscale entropy, stabilogram diffusion analysis, and sway density measures, were examined. After matching, no CoP metric differed significantly between groups. However, SHAP-based exploratory analysis suggested that non-linear features related to temporal structure and multiscale organization contributed more prominently to model output than conventional magnitude-based metrics. Given the limited sample size, these findings should be interpreted as exploratory and hypothesis-generating. Full article

Background: The enzymatic saccharification of cellulose is governed by heterogeneous reaction environments that deviate from classical Michaelis–Menten behavior. Methods: Fractal kinetics were applied to describe the hydrolysis of microcrystalline cellulose (Avicel PH-101) and pretreated hemp hurds using Cellic CTec2. Optimal enzyme loading was first established on Avicel, and the influence of mixing regimes was evaluated. Results: Rotational agitation markedly improved hydrolysis efficiency. Organosolv-based pretreatments generated cellulose-enriched substrates that exhibited higher reactivity than Avicel, while redeposited lignin showed minimal inhibitory effects. Enzyme adsorption studies revealed substantial binding to lignocellulosic substrates, suggesting nonspecific interactions and crowding effects that influence kinetic parameters. Conclusions: Fractal coefficients k and h successfully captured differences in substrate accessibility and reactivity, demonstrating the suitability of fractal models for describing cellulose saccharification in complex solid–liquid systems. Organosolv pretreatment allows a high degree of saccharification, whereas redeposited lignin does not interfere with the enzymatic reaction. Full article

Sea-surface reflections and wind–wave motion render maritime channels strongly time-varying and statistically non-stationary, while nearshore deployments face sparse infrastructure and co-channel multiuser interference. This study integrates reconfigurable intelligent surfaces (RISs) with rate-splitting multiple access (RSMA) for joint online resource allocation. A physics-inspired time-varying channel model is established by embedding fractional Brownian motion-driven slow statistical drift and reflection-phase perturbations. With imperfect, delayed channel state information (CSI) and discrete RIS phase quantization, a proportional-fairness utility maximization problem is formulated to jointly optimize shore base-station precoding, RIS phase shifts, and RSMA common-rate allocation. To cope with strong non-convexity, high dimensionality, mixed continuous–discrete coupling, and partial observability, a fractal-aware recurrent robust Actor–Critic (FRRAC) algorithm is developed. FRRAC encodes short observation histories using a gated recurrent unit and incorporates a lightweight Hurst-proxy estimator to capture slow channel statistics for robust value evaluation and policy learning. Truncated quantile critics and mixed prioritized–uniform replay further improve value robustness, training stability, and sample efficiency. Simulation results show that FRRAC converges faster and more stably under both conventional and fractal non-stationary channel modeling, and outperforms representative baselines across the objective and multiple statistical metrics, validating its effectiveness for joint resource optimization in maritime RIS–RSMA systems. Full article

Background: Successful healing of chronic apical periodontitis after endodontic treatment requires a reduction in the size of the radiolucent area and the healing of the bone. This study aimed to compare the effects of different irrigation activation techniques on healing in single-rooted mandibular premolar teeth with periapical lesions of endodontic origin. Methods: A total of 132 systemically healthy patients with mandibular single-rooted premolar teeth and a periapical index (PAI) score ≥ 3 were assigned to five experimental groups (Sonic activation, Passive ultrasonic irrigation, Photon-Induced Photoacoustic Streaming, Shock Wave Enhanced Emission Photoacoustic Streaming and Manual dynamic activation) and a control group (Conventional Syringe Irrigation). After access cavity preparation, the canals were prepared up to three sizes larger than the initial apical diameter with 5 mL of 2.5% NaOCl used between each file. Final irrigation was performed via the assigned activation system. The root canals were obturated with gutta-percha in a single visit. The effects of the activation systems on healing were compared at 1-year follow-up. The primary outcome measure was the change in lesion diameter. PAI score and fractal dimension (FD) were evaluated as secondary outcomes. Results: At the 1-year follow-up, FD values significantly increased, PAI scores and lesion size decreased in all groups compared with baseline (p < 0.001). However, the increase in FD was comparable among the irrigation groups (p > 0.05). In contrast, lesion size reduction and PAI-based healing rates favored the laser-activated groups. The PAI scores and lesion size in the control group were significantly greater than that in the laser groups (p < 0.05). Conclusions: At the 1-year follow-up, all the groups presented similar FD increases, while the laser irrigation groups presented significantly greater reductions in lesion size than did the control group. Full article

The accelerated pace of urbanization has intensified the urban heat island effect and deteriorated air quality, adversely affecting residents’ living environments and physical health. Community parks serve as the most accessible “terminal units” within the urban green space system, making research on their pollutant concentration reduction capabilities highly relevant. Existing studies predominantly focus on the impact of city-scale green spaces or localized plant arrangements on air pollution, lacking a systematic exploration of synergistic reduction effects across multiple pollutants. To address this gap, six community parks with distinct spatial patterns of green spaces in Zhengzhou were selected as study sites. Six representative indicators of the spatial pattern of green spaces were extracted. Field measurements of PM_2.5 and PM₁₀ concentrations were conducted using a combination of control points and transect sampling methods. Correlation and linear regression analyses were employed to investigate the mechanisms by which the spatial pattern of green spaces in community parks influences PM_2.5 and PM₁₀ reduction. We aimed to investigate the pollutant concentration reduction boundaries of community parks of varying scales, as well as their synergistic effects and differences in reducing PM_2.5 and PM₁₀ concentrations. Results indicate the following: (1) The area, perimeter, and area-weighted shape index of community park green patches showed significant positive correlations with PM_2.5 and PM₁₀ reduction capacity, while fractal dimension, shape index, and proximity index did not exhibit correlations; (2) larger green space patches expand the reduction boundaries for both PM_2.5 and PM₁₀; (3) community parks exhibit a positive synergistic trend in reduction rates for both pollutants. When park areas range between 2 × 10⁴ and 4 × 10⁴ m², their reduction effects show a significant synergistic increase; and (4) community parks with similar spatial configurations but differing canopy closure exhibit varying PM_2.5 and PM₁₀ reduction capacities. These findings provide theoretical foundations and empirical references for optimizing the design of community park green spaces and enhancing ecological benefits. Full article

Background: Freight allocation is a vital decision in distribution logistics to minimize costs and gain environmental benefits. In this paper, we address the problem of freight allocation optimization on an HSR intermodal network with application for the Ottawa–Quebec City corridor where the HSR system will be constructed. Methods: We develop a novel allocation method in which GNNs encode the intermodal network topology and spatial features, while RL agents learn adaptive freight routing policies through reward optimization, which is enhanced by fractal accessibility metrics for spatial connectivity and MCDM for balancing cost, emissions, and service objectives as well as optimizing dynamic freight flows. The model incorporates geospatial data (population, distance), operational factors (demand, costs), and environmental or policy considerations. Addressing the gap in dynamic, multi-criteria cold-climate HSR freight allocation models for North America, we test our framework on the Ottawa–Quebec corridor. Results: The result shows that compared to traditional methods, the five-hub configuration reduces costs by 15–22% and emissions by 20–28%, while the 11-hub model maintains 94%+ service coverage with an 8–12% efficiency trade-off. Conclusions: The conclusion indicates that the HSR intermodal network is more efficient than road only. Sensitivity analysis highlights that key allocation offers policymakers and logistics planners actionable insights for balancing efficiency and accessibility in HSR freight networks. Full article

Alzheimer’s disease (AD) is the most prevalent form of dementia, and accessible biomarkers for early detection remain limited. This study introduces a biomimetic approach in which brain electrical activity is transformed into sound and vibration, emulating natural sensory encoding mechanisms. Resting-state EEG recordings from 36 AD patients and 29 healthy controls were averaged by group, directly sonified, and used to drive a membrane–laser system that projected dynamic vibrational patterns. This transformation mirrors how biological systems convert electrical signals into sensory representations, offering a novel bridge between neural dynamics and physical patterns. The resulting videos were processed through adaptive binarization, morphological filtering, and contour-based masking. Quantitative descriptors such as active area, spatial entropy, fractal dimension, and centroid dynamics were extracted, capturing group-specific differences. A Random Forest classifier trained on these features achieved an accuracy of 0.85 and an AUC of 0.93 in distinguishing AD from controls. These findings suggest that EEG sonification combined with vibrational projection provides not only a novel non-invasive biomarker candidate but also a biomimetic framework inspired by the brain’s own capacity to encode and represent complex signals. Full article

As a key indicator for measuring urban green visibility, the Green View Index (GVI) reflects actual visible greenery from a human perspective, playing a vital role in assessing urban greening levels and optimizing green space layouts. Existing studies predominantly rely on single-source remote sensing image analysis or traditional statistical regression methods such as Ordinary Least Squares and Geographically Weighted Regression. These approaches struggle to capture spatial variations in human-perceived greenery at the street level and fail to identify the non-stationary effects of different drivers within localized areas. This study focuses on the Luolong District in the central urban area of Luoyang City, China. Utilizing Baidu Street View imagery and semantic segmentation technology, an automated GVI extraction model was developed to reveal its spatial differentiation characteristics. Spearman correlation analysis and Multiscale Geographically Weighted Regression were employed to identify the dominant drivers of GVI across four dimensions: landscape pattern, vegetation cover, built environment, and accessibility. Field surveys were conducted to validate the findings. The Multiscale Geographically Weighted Regression method allows different variables to have distinct spatial scales of influence in parameter estimation. This approach overcomes the limitations of traditional models in revealing spatial non-stationarity, thereby more accurately characterizing the spatial response mechanism of the Global Vulnerability Index (GVI). Results indicate the following: (1) The study area’s average GVI is 15.24%, reflecting a low overall level with significant spatial variation, exhibiting a “polar core” distribution pattern. (2) Fractal dimension, normalized vegetation index (NDVI), enclosure index, road density, population density, and green space accessibility positively influence GVI, while connectivity index, Euclidean nearest neighbor distance, building density, residential density, and water body accessibility negatively affect it. Among these, NDVI and enclosure index are the most critical factors. (3) Spatial influence scales vary significantly across factors. Euclidean nearest neighbor distance, building density, population density, green space accessibility, and water body accessibility exert global effects on GVI, while fractal dimension, connectivity index, normalized vegetation index, enclosure index, road density, and residential density demonstrate regional dependence. Field survey results confirm that the analytical conclusions align closely with actual greening conditions and socioeconomic characteristics. This study provides data support and decision-making references for green space planning and human habitat optimization in Luoyang City while also offering methodological insights for evaluating urban street green view index and researching ecological spatial equity. Full article

Objective: Pediatric cancer, though less prevalent than adult malignancies, constitutes a significant public health concern due to its long-term effects on survival, development, and quality of life. This study aimed to investigate spatial patterns and temporal trends of pediatric cancer in Romania over a ten-year period (2008–2017), identifying persistent and emerging geographic hotspots using Geographic Information Systems (GIS)–based modelling and spatial statistics. Methods: A national pediatric cancer registry provided by the Ministry of Health was analyzed for cases among individuals aged 0–18 years, categorized by administrative-territorial units (ATUs), ICD-10 codes, sex, and year. Spatial indicators of persistence (recurrent prevalence across multiple years) and continuity (uninterrupted recurrence) were computed. Hotspot analysis was conducted using Local Moran’s I, and trend patterns were assessed through temporal modeling. Additionally, fractal and complexity metrics were applied to characterize the spatial structure and heterogeneity of cancer persistence and continuity across regions. Results: Although national pediatric cancer prevalence exhibited a modest decline from 3.57‰ in 2008 to 3.44‰ in 2017, GIS-based spatial modeling revealed stable high-risk clusters in Central and South-Eastern Romania, particularly in historically industrialized counties such as Hunedoara, Prahova, and Galați. These correspond to regions with past heavy industry and chemical pollution. Male children presented a higher frequency of malignant tumors (48,502 cases in males vs. 36,034 in females), while benign and uncertain-behavior neoplasms increased more prominently among females (from 3847 to 4116 cases, compared with 3141 to 3199 in males). Several rural localities showed unexpected prevalence spikes, potentially associated with socioeconomic deprivation, limited health literacy, and reduced access to pediatric oncology services. Regional disparities in diagnostic and reporting capacities were also evident. Conclusion: GIS-based spatial epidemiology proved effective in revealing localized, sex-specific, and persistent disparities in pediatric cancer across Romania. The integration of spatial indicators and complexity metrics into national cancer control programs could strengthen early detection, optimize resource allocation, and reduce health inequities. These findings highlight the value of combining geospatial analysis and fractal modeling to guide evidence-based public health strategies for pediatric oncology. Full article

Background: This paper develops a novel, interdisciplinary framework for optimizing high-speed rail (HSR) freight logistics hubs in the Ottawa–Quebec City corridor, addressing critical gaps in geospatial mismatches, static optimization limitations, and narrow sustainability scopes found in the existing literature. Methods: The research methodology integrates a hybrid graph neural network-reinforcement learning (GNN-RL) architecture that encodes 412 nodes into a dynamic graph with adaptive edge weights, fractal accessibility (α = 1.78) derived from fractional calculus (α = 0.75) to model non-linear urban growth patterns, and a multi-criteria sustainability evaluation framework embedding shadow pricing for externalities. Methodologically, the framework is validated through global sensitivity analysis and comparative testing against classical optimization models using real-world geospatial, operational, and economic datasets from the corridor. Results: Key findings demonstrate the framework’s superiority. Empirical results show an obvious reduction in emissions and lower logistics costs compared to classical models, with Pareto-optimal hubs identified. These hubs achieve the most GDP coverage of the corridor, reconciling economic efficiency with environmental resilience and social equity. Conclusions: This research establishes a replicable methodology for mid-latitude freight corridors, advancing low-carbon logistics through the integration of GNN-RL optimization, fractal spatial analysis, and sustainability assessment—bridging economic viability, environmental decarbonization, and social equity in HSR freight network design. Full article

The assessment of forest health and terrain usability is closely tied to slope accessibility. Current methods for evaluating terrain accessibility based solely on slope characteristics often lack precision and fail to capture the combined effects of topography and vegetation. This study introduces succolarity, together with succolarity reservoir and delta (Δ) succolarity, as fractal-based measures for assessing undeveloped land accessibility. The analysis focused on two test areas: the Ceahlău Mountains and the Blaj–Vulpăr Hills. Results revealed lower accessibility values for the Ceahlău Mountains (0.01 to 0.23 for slopes of 0–5° and 0–30°) compared to the Blaj–Vulpăr Hills (0.035 to 0.598 for the same ranges). These significant contrasts demonstrate that terrain fragmentation and compact forests act as decisive constraints, with slope predominating in mountains and vegetation in hilly areas. The findings are valuable for environmental agencies, emergency services, and research groups studying land morphology and mobility. Practical applications include infrastructure planning, sustainable land-use management, and strategic operations in remote terrains. Incorporating additional datasets (e.g., hydrographic networks, seasonal vegetation) and refining methodologies will further enhance succolarity-based assessments, supporting sustainable development in challenging environments. Full article

Regional comprehensive transportation infrastructures constitute the fundamental basis for the development of inland urban agglomerations. To elucidate the role of comprehensive transportation in shaping the spatial organization and expansion of urban agglomerations, this study takes the Yangtze River Middle Reaches Urban Agglomeration (YRMRUA) as a case example. It examines the spatial relationships between transportation network layout and spatial expansion patterns using fractal dimension based on traffic accessibility, traffic-weighted linear density, and Pearson correlation analysis. The key findings of this study are as follows: (1) The YRMRUA exhibits a partial fractal growth pattern influenced by transportation development, which indicates that the comprehensive transportation has a significant but limited impact on YRMRUA. (2) There is a moderate correlation between traffic-weighted linear density and spatial expansion intensity within YRMRUA. (3) Specific groups such as the Wuhan–Ezhou–Huanggang–Huangshi group, Changsha–Zhuzhou–Xiangtan group, and Nanchang–Yichun group have formed in areas where transportation development and spatial expansion are at the forefront. (4) Different modes of transportation, including waterway transportation, railway transportation, and road transportation, have varying effects on spatial expansion. The integration of these modes forms the fundamental framework of urban agglomerations. Full article