Search Results (2,745)

Fused deposition modeling (FDM) is a material-extrusion additive manufacturing technology that is widely used in rapid prototyping, complex product modeling, and functional part fabrication. However, process-parameter drift and environmental disturbances may induce underfilling, overfilling, warping, delamination, and other defects, thereby reducing part quality or interrupting the manufacturing process. Since FDM is characterized by point-wise extrusion and layer-by-layer deposition, layer-surface images naturally contain both spatial morphology and temporal evolution information. Existing image-based diagnostic methods often treat layer images as independent samples, and the selection of the image-stream length is still insufficiently supported by experimental evidence. Moreover, spatial compression in spatiotemporal neural networks may remove local defect information that is important for distinguishing similar process-parameter drifts. This study provides a deployment-oriented analysis of FDM image-stream diagnosis by systematically examining how layer-window length, spatial feature preservation, and strict data partitioning influence process-parameter drift recognition. To address these issues, this paper studies ConvLSTM-based FDM image-stream process-parameter drift diagnosis. Continuous region-of-interest image streams are constructed for one nominal condition and six process-parameter drift conditions. In this paper, the time step T denotes the number of consecutive layer-surface images, or, equivalently, the number of consecutive printed layers, contained in one diagnostic image stream. A ConvLSTM-Flatten baseline is first developed to preserve complete spatial feature maps and to evaluate the effect of different time-step lengths. Then, a ConvLSTM model with adaptive spatial pooling and temporal attention (ASP-TA) is constructed to analyze the influence of spatial pooling granularity and temporal feature fusion. The experiments show that the ConvLSTM-Flatten model achieves the highest average test accuracy of 0.7288 at $T=9$, whereas $T=3$ is identified as a practical optimal time step when test accuracy, image-frame computation, diagnosis latency, and convergence behavior are considered together. The paired trial-wise accuracy difference between $T=9$ and $T=3$ is small and not statistically significant over ten repeated trials. Thus, the diagnostic window corresponding to $T=3$ covers three consecutive deposited layers; after the initial window is available, stride-one stream construction allows the diagnosis to be updated with each newly acquired layer image. ASP-TA with a pooling size of eight consistently outperforms ASP-TA with a pooling size of four, but both are lower than the Flatten baseline, indicating that preserving sufficient spatial information is essential for distinguishing FDM process-parameter drift states. The results reveal the non-monotonic influence of time-step length and clarify the tradeoff between spatial feature preservation and model compactness in FDM image-stream process-parameter drift diagnosis. Full article

Highway corridors are increasingly being discussed not only as zones of ecological disturbance but also as components of regional green infrastructure with potential carbon sequestration functions, yet their long-term evolutionary characteristics and multi-scale associated factors remain insufficiently understood. Using multi-source time-series data from 2000 to 2023, we developed an analytical framework integrating the CASA model, Random Forest, and geographically weighted regression (GWR). To ensure methodological rigor, we implemented a Spatial K-fold Cross-Validation strategy and incorporated Partial Dependence Analysis (PDA) to identify non-linear thresholds. The results indicate that: (1) Vegetation carbon sequestration within Shandong’s highway corridors increased significantly, with total sequestration rising from 5.54 × 10⁶ t in 2000 to 1.55 × 10⁷ t in 2023, representing an average annual growth rate of approximately 5.0%. This growth transitioned from a relatively stable phase to a more rapid growth phase. (2) A clear distance-related ecological pattern was observed. Statistical tests (Kruskal–Wallis H test) confirmed that vegetation carbon sequestration exhibited a significant non-monotonic gradient ($p<0.05$), with a stable peak zone observed 50–100 m from the roadbed. This peak zone is associated with a spatial “trade-off” pattern between the attenuation of traffic-related stressors and roadside ecological management. (3) The observed spatial pattern was associated with a nonlinear coupling of natural background conditions and human disturbance. Precipitation and temperature were the dominant associated factors, while PDA further identified a critical precipitation threshold (~750 mm) and localized tipping points for human interference, with a distinct road-disturbance-sensitive zone evident within 200–500 m. The results suggest that high-standard ecological design and active restoration measures are associated with lower ecological disturbance and higher vegetation carbon sequestration performance in some highway corridors. However, these relationships should be interpreted cautiously, as they may also be influenced by differences in climate background, topography, land-use context, and road construction history. These findings provide empirical evidence to inform differentiated ecological restoration and low-carbon management of traffic corridors. Full article

Archaeological feature detection at complex, mixed-environment sites requires accurate, efficient methods for identifying subtle morphological signatures. This study presents a semi-automated remote sensing pipeline for the detection and delineation of archaeological earthworks at Cahokia Mounds (Illinois, USA), a major Mississippian urban center and UNESCO World Heritage Site. Three LiDAR datasets, two collected via UAV-mounted sensors and one from a piloted aircraft survey, were processed into Digital Terrain Models and transformed into Local Relief Models (LRM). K-means clustering was applied to segment the LRMs into feature classes, followed by contour bounding using the OpenCV library to outline mounds and borrow pits. Additionally, SAR-derived Local Incidence Angle (LIA) rasters from PALSAR-3 and Sentinel-1 were processed through angular deviation mapping to identify slope anomalies associated with archaeological features. Results across all five datasets demonstrate the complementary strengths of LiDAR and SAR: LiDAR excels at resolving elevation-defined features such as mound footprints, while LIA captures directional slope behavior that highlights mound edges, borrow pit rims, and linear features such as causeways. Comparative analysis of LiDAR acquisition frequencies reveals minimal differences in archaeological feature recovery between pulse settings, suggesting that sensor platform choice matters more than power-density tradeoffs for this application. Despite the need for human review to filter modern disturbances and natural false positives, the integrated workflow meaningfully accelerates prospection and reduces interpretive subjectivity. The methods are scalable, site-invariant, and work with open-access data, making them applicable to archaeological landscapes worldwide. Full article

Conventional static approaches to cultivated land quality (CLQ) assessment often fail to capture the rapid spatial restructuring of cultivated land in urbanizing regions. This study takes Chengdu, China, as the study area and employs multi-source and multi-indicator datasets from 2010, 2017, and 2023 to assess CLQ using an integrated AHP-CRITIC weighting approach, combined with obstacle degree and constraint factor analyses. The results show that the mean CLQ score increased from 0.520 in 2010 to 0.695 in 2023, reflecting the continuous improvement in stable cultivated land quality. Constraint factors also shifted from natural endowment limitations to engineering- and management-related disturbances: converted land was mainly constrained by climatic and topographic conditions, newly added land by soil moisture and fertility after land-use conversion, and stable land by compound soil-water and terrain constraints. These findings provide scientific evidence and practical references for high-standard farmland construction and refined cultivated land governance in rapidly urbanizing grain-producing regions. Full article

The coast redwood forest, populated by the ancient relict species Sequoia sempervirens, provides unique and essential ecological services along the Pacific coast of California. It is a haven for endemism and ecological diversity, offers habitat for threatened species, and is an important global terrestrial carbon sink. However, a long history of resource extraction has significantly impacted this ecosystem. Complex old-growth forests have largely been replaced with managed timber stands, and biological diversity has been reduced through the loss of habitat and basic ecological functions. Under natural conditions, coast redwood is highly resilient to disturbance, due to its propensity for basal and epicormic sprouting. The primarily clonal reproductive strategy of S. sempervirens allows for natural thinning as a stand matures, generally leading to the development of late-seral characteristics without the need for active restoration. The increasingly pervasive use of active silvicultural tools for restoration, such as forest thinning and commercial timber harvest, can create a density-driven cycle that requires periodic re-application of the treatment and hinders natural successional processes. In order to restore forest health and resiliency, natural successional processes inherent to coast redwood can be supported as a restoration alternative. Full article

Climate change is increasingly altering the ecological dynamics of apple orchard ecosystems, creating new challenges for sustainable management of phytophagous mites. Rising temperatures, prolonged drought periods, and increasing climatic variability influence mite population dynamics, destabilize predator–prey interactions, and reduce the effectiveness of traditional pest management approaches. This review examines sustainable mite management in apple orchards through the interconnected perspectives of ecological stability, climatic stress, and resilience-oriented agroecosystem management. Particular attention is given to the ecological mechanisms underlying mite outbreaks, including climate-driven acceleration of reproduction, trophic destabilization, biodiversity loss, and disruption of biological regulation processes. The ecological limitations of both conventional chemical control and biological control strategies are critically analyzed, highlighting issues related to pesticide-induced ecological disturbance, resistance development, climatic sensitivity of natural enemies, and operational constraints. The review further explores resilience-oriented management frameworks based on ecological intensification, habitat diversification, conservation biological control, adaptive management, and system-oriented regulation. Current research gaps are identified, including the lack of long-term ecological studies, insufficient integration of climatic and ecological datasets, limited development of resilience indicators, and underrepresentation of continental and semi-arid orchard systems. The findings suggest that future sustainable mite management should move beyond reactive pest suppression toward ecosystem-based approaches that strengthen ecological resilience and adaptive capacity under increasing climatic uncertainty. Full article

Wildfires are a dominant ecological disturbance in Mediterranean ecosystems, yet how post-fire aboveground carbon dynamics and vegetation characteristics govern soil organic carbon stock (SOC) remains poorly understood. This study characterized the dynamics of the carbon pool and changes in the plant community in cork oak shrublands in southern Portugal 11 and 19 years after a fire. Unburned stands were used as a reference. Five plots of each scenario were selected, for a total of 45 independent transects (15/scenario). Aboveground carbon, litter carbon, SOC, and community structural and diversity traits were quantified. Random Forest regression was used to identify the structural and compositional predictors at each stage. The results showed that 11 and 19 years after the fire, the stands held approximately 3:1 and 2:1 more aboveground carbon than the unburned sites due to higher post-fire shrub growth. Total litter carbon amount reached the highest value at 19 years, accompanied by a transient increase in species richness. However, SOC did not differ significantly across any scenario, revealing a clear decoupling between above- and belowground pools, likely constrained by Mediterranean drought conditions. Random Forest analysis showed that the nature of the vegetation–SOC relationships shifted qualitatively across the chronosequence, from structurally dominated in unburned stands to increasingly species-identity-driven. These findings highlight the limitations of assuming monotonic post-fire carbon recovery and underscore the role of species functional identity in mediating long-term SOC dynamics in Mediterranean shrublands. Full article

Background/Objectives: Estrogen deficiency is associated with metabolic disturbances and impaired glucose homeostasis. Morin, a natural flavonol, has shown promising hypoglycemic and antioxidant properties, but its effects under hypoestrogenic diabetic conditions remain poorly understood. The aim of this study was to evaluate the effects of morin on body weight, fasting blood glucose, glucose tolerance, and selected serum biochemical markers in an experimental model of diabetes under estrogen-deficient conditions (ovariectomized diabetic female mice). Methods: Female CD1 mice underwent sham surgery or ovariectomy (OVX), and each surgical condition was further divided into non-diabetic and diabetic subgroups treated with vehicle, glibenclamide (10 mg/kg), or morin (30 mg/kg). Body weight and fasting blood glucose were monitored over a 15-day treatment period. Oral glucose tolerance was assessed on day 15, and serum biochemical markers, including glucose, cholesterol, triglycerides, uric acid, blood urea nitrogen, creatinine, ALT, and AST, were measured thereafter. Results: Ovariectomy aggravated diabetes-associated hyperglycemia, impaired glucose tolerance, and triglyceride elevation. Morin treatment reduced fasting blood glucose and improved glucose tolerance in diabetic mice, including ovariectomized animals. Morin also attenuated the increase in serum triglycerides and blood urea nitrogen in ovariectomized diabetic mice, although it did not significantly improve cholesterol, uric acid, creatinine, ALT, or AST levels. Compared with glibenclamide, morin showed relevant glucose-lowering activity but had a more limited effect on the overall biochemical profile. Conclusions: These findings suggest that morin may partially improve glycemic control and selected metabolic alterations in experimental diabetes associated with estrogen deficiency. Further studies are required to clarify its mechanisms of action, long-term efficacy, and translational relevance. Full article

Coupled nitrogen (N) and phosphorus (P) cycling in calcareous karst soils, and how it responds to long-term land use and restoration, remains poorly quantified. We compared seven plots on a karst slope platform: three development types (degraded disturbed land, pasture, and fruit orchard) and four restoration types (planted evergreen forest, planted deciduous forest, evergreen–deciduous mixed forest, and naturally restored forest). Gross N transformation rates were measured by ¹⁵N isotope dilution, alongside soil properties, available P, microbial biomass N, and enzyme activities. Conservation plots generally had higher soil organic carbon, total N, microbial biomass N, and enzyme activity than development plots; soil organic carbon peaked under naturally restored forest (57.5 g·kg⁻¹) and was lowest in disturbed land (47.9 g·kg⁻¹). Naturally restored forest also showed the highest gross nitrification and total N mineralization, whereas disturbed land had the weakest ammonification, with negative gross rates pointing to N immobilization. Available P (up to 15.9 mg·kg⁻¹) tracked alkaline phosphatase activity, organic carbon, and total N rather than total P. Across the alkaline range (pH 7.2–7.8), random forest models ranked ammonium and enzyme activity, not pH, as the main predictors of N mineralization. Long-term land use and restoration were thus associated with consistent differences in karst soil N and P supply. Full article

Idiopathic normal pressure hydrocephalus (iNPH) is a potentially reversible neurological disorder characterized by gait disturbance, cognitive impairment, and urinary incontinence; however, its diagnosis and prediction of shunt responsiveness remain challenging. This systematic review aimed to synthesize current evidence on cerebrospinal fluid (CSF) proteomic biomarkers in iNPH and to identify molecular patterns with diagnostic and prognostic relevance. A PRISMA-guided search of PubMed, Web of Science, and Google Scholar identified 14 eligible studies comprising 1171 iNPH patients. Proteomic analyses revealed substantial heterogeneity in study design and detected proteins; however, consistent patterns emerged. iNPH is associated with upregulation of inflammatory and extracellular matrix-related proteins and relative downregulation of synaptic and neuronal markers. Neurodegenerative proteins, including amyloid-β, tau, and neurofilament light chain, demonstrated value in differentiating iNPH from comorbid neurodegenerative diseases and in predicting response to ventriculoperitoneal shunting (VPS). These findings support a multifactorial model of iNPH involving impaired glymphatic clearance, neuroinflammation, blood–brain barrier dysfunction, and mechanical axonal stress. Multidimensional biomarker profiles, rather than single proteins, appear to provide the greatest clinical utility, highlighting the need for standardized proteomic panels and integrative predictive models. However, given the substantial heterogeneity of the included studies and the predominantly exploratory nature of current proteomic evidence, the identified proteins should be interpreted as candidate biomarkers rather than clinically validated diagnostic or prognostic tools. Multidimensional biomarker profiles appear biologically plausible and may offer greater explanatory value than single proteins, but their clinical utility requires validation in standardized prospective cohorts. The authors therefore propose a conceptual iNPH proteomic “Vulnerability Model” integrating CSF biomarkers to reflect the balance between reversible and irreversible pathology; this is currently a hypothetical model that requires rigorous statistical and clinical validation through large-scale prospective cohort studies before it can fulfill its potential for improving patient stratification and prediction of postoperative outcomes. Full article

Abandoned pastoral settlements can create disturbed and nutrient-enriched microsites that favor the dominance of native expansive plant species. Yet limited empirical evidence exists on how abandoned Maasai bomas influence the spread of Urtica massaica and associated plant community changes in the Ngorongoro Conservation Area, a UNESCO World Heritage Site in Tanzania. This study assessed the influence of abandoned bomas on plant species abundance, richness, diversity, soil seedbank status, and the spatial distribution of U. massaica. A multistage stratified random sampling design was used, whereby Ngorongoro and Nainokanoka zones were selected from the designated management zones of the conservation area. Vegetation data, soil samples, and geographic coordinates of abandoned bomas were collected from abandoned boma sites and adjacent control sites. Plant species abundance, richness, and diversity were compared between abandoned bomas and control sites after testing data normality using the Shapiro–Wilk test. Independent-sample t-tests were used for normally distributed data, while Wilcoxon rank-sum tests were used for non-normally distributed data. Spatial distribution of U. massaica was assessed using GIS-based heatmap and kernel density estimation. Results showed that native plant species abundance was significantly higher in control sites than in abandoned bomas. Plant species richness and diversity also differed significantly between sites in both Ngorongoro and Nainokanoka, with control sites supporting higher richness and diversity. However, soil seedbank results showed no significant differences in species richness and diversity between soils collected from abandoned bomas and control sites, although slightly higher values were observed in control soils. Spatial analysis revealed that U. massaica hotspots were concentrated mainly in highland areas with high densities of abandoned bomas. These findings suggest that abandoned bomas may act as focal points for U. massaica establishment and dominance, reducing aboveground plant diversity while retaining some potential for natural regeneration through the soil seedbank. Management interventions should prioritize abandoned bomas as key sites for controlling U. massaica spread and supporting vegetation recovery in the Ngorongoro Conservation Area. Full article

Background: Research on social media use, fear of missing out (FoMO), sleep disturbance, and health complaints has been dominated by survey-based studies, particularly among adolescents and university students. Less is known about how users spontaneously describe these experiences in naturalistic online settings. This exploratory pilot study examined how publicly available Reddit discussions narrate the relationship between social media use, FoMO-related concern, sleep disruption, and self-reported physical complaints. Methods: A total of 30 publicly available English-language Reddit posts and comments were purposively sampled from 11 threads dated August 2022 to March 2026. The study used exploratory qualitative content analysis supported by reflexive thematic interpretation. Structured indicators were used to describe whether each unit contained explicit FoMO language, implicit FoMO-related concern, sleep disturbance, physical health complaints, and nighttime use or sleep loss. Thematic coding was used to identify dominant discourse patterns. All counts and percentages are reported only to characterize the analytic corpus and should not be interpreted as prevalence estimates. Results: Within the corpus, sleep disturbance appeared in 16 of 30 units, nighttime use or sleep loss in 15, physical health complaints in 11, explicit FoMO language in 6, and implicit FoMO-related concern in 3. The dominant themes were delayed sleep and bedtime displacement, somatic and cognitive overload, self-regulation and recovery, and compulsive monitoring and comparison. Sleep-related complaints were usually described alongside bedtime scrolling, delayed disengagement, or lost sleep opportunity. FoMO-related concern was less often expressed through formal terminology and more often appeared through everyday descriptions of checking, comparison, and difficulty disconnecting. Conclusions: This small exploratory corpus suggests that Reddit users often describe social media-related strain through practical behavioral language, such as late-night scrolling, inability to stop, lost sleep, next-day fatigue, headache, and brain fog. The findings are descriptive, discourse-focused, and hypothesis-generating. They do not estimate population prevalence or establish causal health effects. To improve transparency, the revised study provides a de-identified analytic matrix of all 30 coded Reddit units and reports a strengthened coding procedure with independent second-coder checking. Naturally occurring online discourse may complement survey-based digital-health research by showing how users themselves frame the embodied experience of digital over-engagement. Full article

Naturally formed treefall gaps represent primary sources of environmental heterogeneity in tropical forests, yet their role in driving the components of beta diversity in specialized leaf-litter fauna remains poorly understood. We investigated the influence of natural treefall gaps on harvestmen (Arachnida: Opiliones) community structure and beta diversity partitioning in a well-preserved Atlantic Forest remnant in southern Bahia, Brazil. Using standardized nocturnal searches and leaf-litter sampling, we recorded 845 individuals across 23 species. Coverage-based rarefaction indicated higher estimated richness in gaps, although observed alpha diversity did not differ significantly among habitats. Community composition differed significantly along the gap–forest gradient, driven mainly by litter depth and microclimatic variation. Indicator species analysis identified Protimesius sp. (Stygnidae) as a robust gap-specialist. Beta diversity partitioning revealed that turnover accounted for 79.5% of total dissimilarity, while nestedness contributed 20.5%. Treefall gaps exhibited the highest internal beta diversity and species exclusivity, supporting their role as dynamic environmental filters that enhance regional diversity. Our findings highlight the ecological importance of natural disturbance and litter structure in maintaining biodiversity patterns in tropical forests. Full article

While terrestrial carbon storage is vital for achieving global carbon neutrality, its spatiotemporal evolution in ecologically fragile regions—such as the Pisha sandstone area—is complicated by intense erosion and complex environmental drivers. Widely known as the Pisha sandstone area, often referred to as the “Earth’s ecological cancer” due to its unique geological instability (“hard as rock when dry, soft as mud when wet”), this area is a critical but vulnerable carbon sink in the Yellow River Basin. This study aims to clarify these dynamics and identify their non-linear driving mechanisms by integrating a coupled PLUS–InVEST model with an XGBoost–SHAP framework to simulate land-use cover change and quantify carbon sequestration potential from 1990 to 2040. Our results reveal: (1) a robust path dependence in land use, where grassland remained the dominant landscape matrix (>75%), which partly explains the stable regional carbon-stock structure and the moderate FoM value of the PLUS validation; (2) carbon storage followed a fluctuating but overall increasing trajectory, projected to reach a peak of 3.19 × 10⁵ tC by 2040 under the Ecological Conservation Scenario (ECS), which significantly outperforms the economic-driven and natural growth modes; (3) hot spot analysis showed that statistically notable low-carbon cold spots were concentrated mainly along valley corridors, marginal transition zones, and locally disturbed patches, whereas high-carbon hot spots were spatially limited; and, (4) crucially, XGBoost–SHAP results should be interpreted as model-based associations rather than direct causal proof; the whole-region model and the regional models jointly suggest that topography, water availability, socioeconomic pressure, and erosion-related factors contribute differently across bare, loess-covered, and sand-covered Pisha sandstone units. These findings support differentiated land-use and restoration strategies rather than uniform regional management. The findings suggest that future management in the Pisha sandstone area should transition from general restoration toward targeted and differentiated regulation to improve regional ecosystem services. Full article

Outlier detection serves as an effective technique for identifying anomalous samples in complex data. Existing methods are often disturbed by noise and boundary samples, which degrade the quality of sample relationships. Moreover, traditional random walk approaches are vulnerable to weak and spurious connections that can mislead the walking process. To address these issues, this paper proposes a robust random walk based on natural neighbors for outlier detection (RWNOD) method. First, an adaptive smoothing mechanism is proposed to leverage natural neighbors to actively adjust sample positions, reducing local noise while preserving structural information. Then, a robust random walk strategy is developed to incorporate shadowed sets into the transition matrix, preserving reliable connections while suppressing unreliable ones. At the same time, a corresponding outlier detection algorithm is proposed. Experiments on datasets are conducted to compare the proposed algorithm with seven other algorithms. The experimental results demonstrate that the proposed algorithm achieves superior performance and strong robustness. Full article