Search Results (1,435)

GPS tracking has made ski injury data abundant, yet few studies have mapped where incidents actually occur or how those patterns differ between skiers and snowboarders. To address this gap, we analyzed 8719 GPS-located incidents (4196 skier; 4523 snowboarder) spanning four seasons (2017–2022, excluding 2019–2020 due to COVID-19) at a large West Coast resort in California. Incidents were aggregated into 45 m hexagons and analyzed using Getis–Ord Gi* hot spot analysis, Local Outlier Analysis (LOA), and a space–time cube with time-series clustering. Hot spot analysis identified both activity-specific and overlapping high-injury concentrations at the 99% confidence level (p < 0.01). The LOA revealed no spatial overlap between skier and snowboarder High-High classifications (areas with high incident counts surrounded by other high-count areas) at the 95% confidence level. Temporal analysis exposed distinct patterns by activity: Time Series Clustering revealed skier incidents concentrated at holiday-sensitive locations versus stable zones, while snowboarder incidents separated into sustained high-activity versus baseline areas. These findings indicate universal safety strategies may be insufficient; targeted, activity-specific interventions may warrant investigation. The methodology provides a reproducible framework for spatial injury surveillance applicable across the ski industry. Full article

This study investigates the phylogenetic relationships, genetic diversity, and biogeographic structure of Pipistrellus species in Türkiye using mitochondrial cytochrome b (Cytb) sequences from 156 specimens collected across 26 localities. Our primary aim was to clarify taxonomic boundaries of morphologically cryptic species and elucidate the evolutionary role of Anatolia in the Western Palearctic. Analyses strongly confirmed that molecular data are mandatory for defining taxonomic boundaries. Crucially, all individuals morphologically identified as P. pygmaeus were genetically determined to be P. pipistrellus, highlighting the inadequacy of external traits for cryptic species. We resolved deep intraspecific divergence across the genus. In P. pipistrellus, two major lineages (Eastern and Western) were identified, partially separated by the Anatolian Diagonal. Their co-occurrence in multiple localities confirms Anatolia’s function as a secondary contact zone. Similarly, P. kuhlii populations represent a transition zone where two distinct lineages, one of Asiatic origin (P. k. lepidus) and one Mediterranean-Levantine (P. k. kuhlii), meet. Furthermore, while P. nathusii is largely associated with migratory European lineages; a genetically distinct, potentially resident lineage was revealed in southwestern Anatolia. Divergence time estimations indicate that this diversification was shaped by major climatic events from the Miocene to the Pleistocene. This study demonstrates that Anatolia is more than just a geographic bridge; it is a dynamic center of evolution, functioning critically as both a glacial refugium and a secondary contact zone for Palearctic bat fauna. Full article

This paper addresses the long-standing question of understanding the origin and evolution of low-frequency unsteadiness interactions associated with shock waves impinging on a turbulent boundary layer in transonic flow (Mach: $1.1$ to $1.3$). To that end, high-speed experiments in a blowdown open-channel wind tunnel have been performed across a convergent–divergent nozzle for different expansion ratios (PR = 1.44, 1.6, and 1.81). Quantitative evaluation of the underlying spectral energy content has been obtained by processing time-resolved pressure transducer data and Schlieren images using the following spectral analysis methods: Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT), as well as coherence and time-lag evaluations. The images demonstrated the presence of increased normal shock-wave impact for PR = 1.44, whereas the latter were linked with increased oblique $\lambda$-foot impact. Hence, significant disparities associated with the overall stability, location, and amplitude of the shock waves, as well as quantitative assertions related to spectral energy segregation, have been inferred. A subsequent detailed spectral analysis revealed the presence of multiple discrete frequency peaks (magnitude and frequency of the peaks increasing with PR), with the lower peaks linked with large-scale shock-wave interactions and higher peaks associated with shear-layer instabilities and turbulence. Wavelet transform using the Morlet function illustrates the presence of varying intermittency, modulation in the temporal and frequency scales for different spectral events, and a pseudo-periodic spectral energy pulsation alternating between two frequency-specific events. Spectral analysis of the pixel densities related to different regions, called spatial FFT, highlights the increased influence of the feedback mechanism and coupled turbulence interactions for higher PR. Collation of the subsequent coherence analysis with the previous results underscores that lower PR is linked with shock-separation dynamics being tightly coupled, whereas at higher PR values, global instabilities, vortex shedding, and high-frequency shear-layer effects govern the overall interactions, redistributing the spectral energy across a wider spectral range. Complementing these experiments, time-resolved numerical simulations based on a transient 3D RANS framework were performed. The simulations successfully reproduced the main features of the shock motion, including the downstream migration of the mean position, the reduction in oscillation amplitude with increasing PR, and the division of the spectra into distinct frequency regions. This confirms that the adopted 3D RANS approach provides a suitable predictive framework for capturing the essential unsteady dynamics of shock–boundary layer interactions across both temporal and spatial scales. This novel combination of synchronized Schlieren imaging with pressure transducer data, followed by application of advanced spectral analysis techniques, FFT, CWT, spatial FFT, coherence analysis, and numerical evaluations, linked image-derived propagation and coherence results directly to wall pressure dynamics, providing critical insights into how PR variation governs the spectral energy content and shock-wave oscillation behavior for nozzles. Thus, for low PR flows dominated by normal shock structure, global instability of the separation zone governs the overall oscillations, whereas higher PR, linked with dominant $\lambda$-foot structure, demonstrates increased feedback from the shear-layer oscillations, separation region breathing, as well as global instabilities. It is envisaged that epistemic understanding related to the spectral dynamics of low-frequency oscillations at different PR values derived from this study could be useful for future nozzle design modifications aimed at achieving optimal nozzle performance. The study could further assist the implementation of appropriate flow control strategies to alleviate these instabilities and improve thrust performance. Full article

Fractal dimension (Frac) and lacunarity (Lac) are frequently proposed as biomarkers of multiscale image complexity, but their incremental value over standardized radiomics remains uncertain. We position both measures within the Image Biomarker Standardisation Initiative (IBSI) feature space by running a fully reproducible comparison in two settings. In a baseline experiment, we analyze $N=1000$ simulated $64\times 64$ textured ROIs discretized to $N_g=64$, computing 92 IBSI descriptors together with Frac (box counting) and Lac (gliding box), for 94 features per ROI. In a wavelet-augmented experiment, we analyze $N=1000$ ROIs and add level-1 wavelet descriptors by recomputing first-order and GLCM features in each sub-band (LL, LH, HL, and HH), contributing $4\times (19+19)=152$ additional features and yielding 246 features per ROI. Feature similarity is summarized by a consensus score that averages z-scored absolute Pearson and Spearman correlations, distance correlation, maximal information coefficient, and cosine similarity, and is visualized with clustered heatmaps, dendrograms, sparse networks, PCA loadings, and UMAP and t-SNE embeddings. Across both settings a stable two-block organization emerges. Frac co-locates with contrast, difference, and short-run statistics that capture high-frequency variation; when wavelets are included, detail-band terms from LH, HL, and HH join this group. Lac co-locates with measures of large, coherent structure—GLSZM zone size, GLRLM long-run, and high-gray-level emphases—and with GLCM homogeneity and correlation; LL (approximation) wavelet features align with this block. Pairwise associations are modest in the baseline but become very strong with wavelets (for example, Frac versus GLCM difference entropy, which summarizes the randomness of gray-level differences, with $\left|r\right|\approx 0.98$; and Lac versus GLCM inverse difference normalized (IDN), a homogeneity measure that weights small intensity differences more heavily, with $\left|r\right|\approx 0.96$). The multimetric consensus and geometric embeddings consistently place Frac and Lac in overlapping yet separable neighborhoods, indicating related but non-duplicative information. Practically, Frac and Lac are most useful when multiscale heterogeneity is central and they add a measurable signal beyond strong IBSI baselines (with or without wavelets); otherwise, closely related variance can be absorbed by standard texture families. Full article

As Canada experiences a growing number of newcomer students with refugee backgrounds, K-12 educators face challenges to meet students’ unique academic, linguistic, and psychosocial needs. This paper examines the role of educational technology (EdTech) to bridge the resource and training gap by enhancing teacher preparedness through an accessible, inclusive, and trauma-informed digital resource. This study presents a qualitative case study methodology to analyze the interactive online manual, Supporting Teachers to Address the Mental Health of Students from War Zones. The research utilizes three data sources: feedback from 110 educators through a questionnaire, observational data from 69 students from two separate pre-service teacher cohorts, and an expert evaluation report conducted by university curriculum specialists. Findings suggest that successful EdTech for refugee-background student initiatives must be trauma-informed, strength-based, culturally responsive, and designed with usability and accessibility in mind. Furthermore, collaboration between K-12 educators, researchers, and developers is vital to ensure that there is alignment of pedagogy and technology. Full article

Osorno volcano (41.1° S, 72° W) is located in the Andean Southern Volcanic Zone. The volcano lies within a national park as part of the protected areas system. This setting provides an opportunity to compare soil microbial communities between sectors with (H) and without (NI) anthropogenic activities within a volcanic territory. To do so, we selected one of the most visited volcanoes in Chilean Patagonia to examine composition, diversity (taxonomic and phylogenetic), and co-presence and mutual exclusion interaction networks between members of volcanic soil bacterial communities. Soil DNA was extracted, and the 16S rRNA gene was analyzed by high-throughput DNA sequencing, followed by taxonomic identification. The most prevalent phylum across all sites (H and NI) was Pseudomonadota, followed by Acidobacteriota, Actinobacteriota, and Chloroflexota. Based on taxonomic and phylogenetic indices, we found that the diversity of bacteria was significantly less in the humanized area than in the non-intervened areas. Beta diversity analysis also revealed a clear separation between humanized and non-intervened soils. Additionally, a decrease in network connectivity was observed at NI sites. Our results provide clear evidence that anthropogenic factors, such as tourism, vehicle parking, and combustion processes, are key drivers shaping bacterial community structure in volcanic soils, with potential consequences for ecosystem health and the capacity to provide ecosystem services. Full article

In the context of fuzzy logic speed control for switching reluctance motor (SRM) applications, the objective of this work is to propose a unique zone-based simplification technique. Using the procedure that has been outlined, it is made easier to reduce membership functions as well as rule sets in a logical manner. This is accomplished by splitting the error–change-of-error plane into discrete decision zones. This method is separate from heuristic or adaptive reduction strategies since it employs a systematic framework that reduces the number of rules from 49 in the standard design to 9 and 5 without compromising the accuracy of the control. This is accomplished without adversely affecting the performance of the control. The simplified controller that was produced as a consequence of this study decreases the amount of overshoot, enhances the speed at which a dynamic response happens, and makes it simpler to use on digital platforms that are affordable. All of these capabilities were achieved by the controller. Based on simulations and testing carried out in the real world, it has been determined that the zone-based simplified fuzzy controller that was proposed has a superior performance to traditional PID and full-rule fuzzy systems in terms of reaction time, stability, and energy efficiency. Taking all of this into consideration, it is evident that it has the potential to be useful in real-world applications for SRM drives that demand a high level of speed while maintaining a low cost factor. Full article

Wearable, rectifiable aerosol photometers (WRAPs), instruments with combined nephelometer and on-board filter-based sampling capabilities, generally show strong correlations with reference instruments across a range of ambient and household PM_2.5 concentrations. However, limited data exist on their performance when challenged by mixed aerosol exposures, such as those found in dusty occupational environments. Understanding how these instruments perform across a spectrum of environments is critical, as they are increasingly used in human health studies, including those in which concurrent PM_2.5 and coarse dust exposures occur simultaneously. The authors collected co-located, ~24 h. breathing zone gravimetric and nephelometer PM_2.5 measures using the MicroPEM v3.2A (RTI International) and the UPAS v2.1 PLUS (Access Sensor Technologies). Samples were collected from adult brick workers (n = 93) in Nepal during work and non-work activities. Median gravimetric/arithmetic mean (AM) PM_2.5 concentrations for the MicroPEM and UPAS were 207.06 (interquartile range [IQR]: 216.24) and 737.74 (IQR: 1399.98) µg/m³, respectively (p < 0.0001), with a concordance correlation coefficient (CCC) of 0.26. The median stabilized inverse probability-weighted nephelometer PM_2.5 concentrations, after gravimetric correction, for the MicroPEM and UPAS were 169.16 (IQR: 204.98) and 594.08 (IQR: 1001.00) µg/m³, respectively (p-value < 0.0001), with a CCC of 0.31. Digital microscope photos and electron micrographs of filters confirmed large particle breakthrough for both instruments. A possible explanation is that the miniaturized pre-separators were overwhelmed by high dust exposures. This study was unique in that it evaluated personal PM_2.5 monitors in a high dust occupational environment using both gravimetric and nephelometer-based measures. Our findings suggest that WRAPs may substantially overestimate personal PM_2.5 exposures in environments with concurrently high PM_2.5 and coarse dust levels, likely due to large particle breakthrough. This overestimation may obscure associations between exposures and health outcomes. For personal PM_2.5 monitoring in dusty environments, the authors recommend traditional pump and cyclone or impaction-based sampling methods in the interim while miniaturized pre-separators for WRAPs are designed and validated for use in high dust environments. Full article

Southern highbush blueberry (SHB, Vaccinium corymbosum, Ericaceae) enables production in warm, low-chill regions, where breeding success depends on precisely timed pollinations. To support breeding in non-traditional environments, we characterized floral staging, anther wall ontogeny, tubule formation, and pollen development in two SHB cultivars (‘Emerald’, ‘Snowchaser’) grown in commercial orchards. Floral development was divided into seven stages: dormant buds (db), five successive floral-bud stages (botA–botE), and anthesis, based on bud size, corolla exposure and pigmentation, and anther/tubule coloration. Internal events were documented by light, confocal, and scanning electron microscopy. External cues reliably separated stages and tracked male-gametophyte phases: meiosis at botB; callose-encased tetrads at botC; permanent tetrahedral tetrads after callose dissolution at botD; bicellular tetrads from botE to anthesis, released intact via poricidal dehiscence. Anther-wall differentiation followed a consistent sequence and lacked a fibrous, lignified endothecium. We therefore propose a new Ericaceous pattern for blueberry anthers, defined by a transient non-lignified subepidermal stratum. Tubules originated apically as solid outgrowths, hollowed centrifugally to a beveled pore, developed a dorsal supportive zone, and mediated poricidal release of permanent tetrads. No qualitative cultivar differences were detected. The staging framework defines operational windows for pollination, emasculation, and pollen handling in low-chill systems. Full article

The fracture behavior of the Al₄Cu₉ intermetallic compound at the interface of impact-welded Cu/Al joints remains insufficiently explored through integrated multiscale modeling and experimental validation. In this study, molecular dynamic (MD) simulations, finite element (FE) analysis implemented in ABAQUS (version 2020) and a cohesive zone model (CZM) were combined with optical microscopy (OM) and scanning electron microscopy (SEM) observations of the interface and crack initiation zones in impact-welded Cu/Al specimens to investigate crack propagation mechanisms under different defect configurations. The experimental specimens consisted of 1060 aluminum (Al) and oxygen-free high-conductivity (OFHC) copper, fabricated via impact welding and subsequently annealed at 250 °C for 100 h. The interfacial morphology and crack initiation features obtained from OM and SEM provided direct validation for the traction–separation (T-S) parameters extracted from MD and mapped into the FE model. The results indicate that composite defects (blunt crack + void) cause a significantly greater reduction in fracture energy and stress intensity factor than single defects and that defect effects outweigh temperature effects within the range of 200–500 K. The experimentally observed crack initiation locations were in strong agreement with simulation predictions. This integrated simulation–experiment approach not only elucidates the multiscale fracture mechanisms of the Al₄Cu₉ interface but also provides a physically validated basis for the reliability assessment and optimization of aerospace Cu/Al welded structures. Full article

The tissue covering the bones in synovial joints is called articular cartilage. Chondrocytes produce and maintain the extracellular matrix and, based on their shape and the orientation of the collagen fibers, articular cartilage is separated into four histological zones: superficial, middle, deep, and calcified zones. Osteoarthritis is a degenerative joint disorder in which mechanical, biochemical, and inflammatory factors contribute to the disruption of the balance between extracellular matrix synthesis and degradation. This article aims to review the literature published to date by identifying the techniques most used in immunohistochemistry and histology for the detection and grading of knee osteoarthritis in rabbit/rat models. A systematic review was carried out using databases to find publications that assessed osteoarthritis in rabbit/rat knee models using histological and immunohistochemical methods. Out of 766 initial articles, 56 met the criteria. Hematoxylin–Eosin and Safranin O demonstrated clear distinctions between healthy and osteoarthritis cartilage. Immunohistochemical findings showed decreased expression of type II collagen and increased expression of matrix metalloproteinases and caspase-3 in osteoarthritis cartilage. Although both have limitations, histology stains are useful for evaluating cartilage structure and osteoarthritis progression. On the other hand, immunohistochemistry techniques support established osteoarthritis processes, including apoptosis, metalloproteinases activity, and collagen degradation. Future research should explore additional pathways to improve osteoarthritis understanding. Full article

L-arginine, a basic amino acid, exhibits high biocompatibility, reactivity, and absorbability. It was selected as the co-polymer modification monomer for L-lactic acid with the objective of enhancing the hydrophilicity of poly(lactic acid) (PLA), neutralizing the acidity of PLA degradation products, and regulating the degradation cycle. The copolymer poly(lactic acid-co-arginine) (PLAA) was synthesized by direct melting polycondensation of L-arginine and L-lactic acid, and the structures and properties of PLAA were characterized. The results indicated the presence of –NH₂, –NH–, and NH= in the molecular chain of the copolymer PLAA. Furthermore, the PLAA was identified as an amorphous copolymer. The “PLAA/CHCl₃/C₆H₁₄” ternary phase diagram was constituted by nonsolvent-induced phase separation (NIPS) by selecting chloroform (CHCl₃) as a good solvent and n-hexane (C₆H₁₄) as a nonsolvent. The phase diagram displays three distinguishable regions: the homogeneous zone, the metastable zone, and the phase separation zone. These regions are identified by the binodal and spinodal curves. The ternary phase diagram establishes a theoretical foundation for the preparation and processing of PLAA nanoparticles, composite materials, and porous fibers or membranes. Full article

Accurate and efficient CFD simulations are essential for a wide range of engineering and scientific applications, from resilient structural design to environmental analysis. Traditional methods such as RANS simulations often face challenges in capturing complex flow phenomena like separation, while high-fidelity approaches including Large Eddy Simulations and Direct Numerical Simulations demand significant computational resources, thereby limiting their practical applicability. This paper provides an in-depth synthesis of recent advancements in integrating artificial intelligence and machine learning techniques with CFD to enhance simulation accuracy, computational efficiency, and modeling capabilities, including data-driven surrogate models, physics-informed methods, and ML-assisted numerical solvers. This integration marks a crucial paradigm shift, transcending incremental improvements to fundamentally redefine the possibilities of fluid dynamics research and engineering design. Key themes discussed include data-driven surrogate models, physics-informed methods, ML-assisted numerical solvers, inverse design, and advanced turbulence modeling. Practical applications, such as wind load design for solar panels and deep learning approaches for eddy viscosity prediction in bluff body flows, illustrate the substantial impact of ML integration. The findings demonstrate that ML techniques can accelerate simulations by up to 10,000 times in certain cases while maintaining or improving the accuracy, particularly in challenging flow regimes. For instance, models employing learned interpolation can achieve 40- to 80-fold computational speedups while matching the accuracy of baseline solvers with a resolution 8 to 10 times finer. Other approaches, like Fourier Neural Operators, can achieve inference times three orders of magnitude faster than conventional PDE solvers for the Navier–Stokes equations. Such advancements not only accelerate critical engineering workflows but also open unprecedented avenues for scientific discovery in complex, nonlinear systems that were previously intractable with traditional computational methods. Furthermore, ML enables unprecedented advances in turbulence modeling, improving predictions within complex separated flow zones. This integration is reshaping fluid mechanics, offering pathways toward more reliable, efficient, and resilient engineering solutions necessary for addressing contemporary challenges. Full article

The radius-to-width ratio has an obvious impact on the flow structure within curved channels, which most natural rivers possess, but there are currently few studies on the influence of the radius-to-width ratio of a tributary (R/B) on the hydrodynamic characteristics of a confluent channel. In order to contribute to this field of research, this study employed the RNG k-ε turbulence model, which has good applicability and accuracy for confluence, to investigate the effects of the R/B and flow ratios (q*) on the hydraulic characteristics of confluence. The results reveal that the numerical model can effectively simulate the velocity distribution in the confluence. The values of the key errors are all relatively small (e.g., the value of Mean RMSE is 0.05), and the flow patterns near the bed and water surfaces are different. The maximum velocity zone (MVZ) and the scale of the separation zone (SZ) increase as R/B increases; conversely, the MVZ and the scale of the SZ decrease as the q* increases. Upstream of the confluence, turbulent kinetic energy (TKE) increases and decreases as R/B and q* increase, respectively, while TKE downstream of the confluence hardly changes. Furthermore, the size of the SF decreases as R/B increases. The value of $\overline{S_w}$ peaks downstream of the confluence, increases with the increase in the R/B, and decreases with the increase in the q*. The results of this study will contribute to a better understanding of the hydrodynamic characteristics of confluence and provide valuable insights for the management and ecological restoration of confluent channels. Full article

Integrating Rights, Restrictions, and Responsibilities (RRR) information within land administration presents a significant challenge. Currently, land rights management and spatial planning in Indonesia are handled by separate institutions within land administration services, leading to fragmented information and potentially inconsistent decisions, and the information about them is siloed. While land registration data typically provide information regarding land rights, the restrictions and responsibilities are derived from spatial planning data, primarily from Detailed Spatial Plans (RDTR). This fragmented data landscape complicates landowners understanding of their rights and obligations, as well as local government in issuing the development permits. This paper proposes a method to integrate RRR elements by overlaying parcel data (representing Rights) with spatial planning data from RDTR (representing Restrictions and Responsibilities). The analysis reveals that challenges arise from discrepancies between parcel boundaries and spatial plan delineations. To address these challenges, problem scenarios have been developed, illustrating situations where a parcel may fall within a single sub-zone, multiple sub-zones, partly outside sub-zone, and no planning zone. The integrated approach herein aims to empower landowners, ease the issuing of development permits by local government, and align with the government’s digital transformation initiatives. Full article