Search Results (1,864)

The Kavokta deposit in Russia contains gray and black dolomite-type nephrite, which is in high demand commercially. Although the fact that black nephrite has been found in several deposits, the reasons for its color are not well understood. The present study aims to identify the localization and mineral composition of gray and black nephrite, and to determine the reasons for its dark coloration. The mineral composition of nephrite was studied using a scanning electron microscope with energy-dispersive microanalysis (SEM-EDX) and X-ray phase analysis. Also, the isotopic composition of carbon in graphite in nephrite and in carbonates associated with nephrite in the surrounding strata was determined. The gray–black color in most samples from the southeastern part of the Kavokta deposit (lodes 17 and 28 of the nephrite-bearing zone 4 of the Medvezhy section and lode 6-1 of the nephrite-bearing zone 6 of the Levoberezhny section) is due to the presence of graphite. Syngenetic graphite formed both by the organic matter buried in dolomites and by the decomposition of carbon dioxide that is released during decarbonation under the influence of deep-seated hydrogen. The color of nephrite also depends on the iron content, changing from white to light green as the iron content increases. The gray color of tremolite–diopside nephrite is due to the development of chlorite aggregates that replace diopside and/or tremolite. The gray-green to black color of the nephrite in the northwestern part of the Kavokta deposit (lode 1 of the nephrite-bearing zone 1 of the Prozrachny section) is due to the high iron content in the tremolite–actinolite at the contact with the epidote–tremolite skarn formed after amphibolite. The identified patterns of black nephrite localization can be used in the process of geological exploration of similar deposits elsewhere in Russia and abroad. Full article

Landscape architecture has long engaged esthetics, ecological process, and cultural meaning, and contemporary practice increasingly embraces systemic and process-based approaches. Yet even within this richness, designers often lack systematic tools for addressing how embodied interaction shapes human–nature relationships. Granted, frameworks such as biophilic design and restorative environments emphasize the importance of contact with nature. Yet they often stop short of specifying the sensory and movement-based interactions through which agency, well-being, and meaning are cultivated. To address this gap, this paper introduces Interaction Pattern Design (IPD) as a theory-grounded and practice-oriented framework for landscape architecture. The first part of the paper outlines what interaction patterns are, how they scale along the continuum from highly domestic to relatively wild environments, and the empirical evidence that establishes their significance. The second half of this paper speaks to designers specifically and applies this IP approach to the design process. Two design tools are introduced. One is Quadrant Mapping, which visualizes intersections of environmental and behavioral wildness within a site. The second is Structuring Interaction Patterns, which organizes design elements through scale, sequence, and co-occurrence. Drawing from case studies, the paper demonstrates how these tools enrich process- and ecology-focused design methods, supporting deeper and more enduring forms of engagement with nature. Full article

Rhinogenic contact point headache (RCPH) represents a diagnostic challenge due to different anatomical presentations and unstandardized imaging markers. This prospective multicenter study involving 120 patients aimed to develop and validate a CT-based imaging framework for RCPH diagnosis. High-resolution CT scans were systematically assessed for seven parameters: contact point (CP) type, contact intensity (CI), septal deviation, concha bullosa (CB) morphology, mucosal edema (ME), turbinate hypertrophy (TH), and associated anatomical variants. Results revealed CP-I (37.5%) and CP-II (22.5%) as predominant patterns, with moderate CI (45.8%) and septal deviation > 15° (71.7%) commonly observed. CB was found in 54.2% of patients, primarily bulbous type (26.7%). Interestingly, focal ME at CP was independently associated with greater pain severity in the multivariate model (p = 0.003). The framework demonstrated substantial to excellent interobserver reliability (κ = 0.76–0.91), with multivariate analysis identifying moderate–severe CI, focal ME, and specific septal deviation patterns as independent predictors of higher pain scores. Our imaging classification system highlights key radiological biomarkers associated with symptom severity and may facilitate future applications in quantitative imaging, automated phenotyping, and personalized treatment approaches. Full article

In slab continuous casting, achieving uniform cooling in the secondary cooling zone is essential for ensuring both surface integrity and internal quality. To optimize the process for ship plate steel, a solidification heat transfer model was developed, incorporating radiation, water film evaporation, spray impingement, and roll contact. The influence of secondary cooling water flow on slab temperature distribution was systematically investigated from multiple perspectives. The results show that a weak cooling strategy is crucial for maintaining higher surface temperatures and aligning the solidification endpoint with the soft reduction zone. Along the casting direction, a “strong-to-weak” cooling pattern effectively prevents abrupt temperature fluctuations, while reducing the inner-to-outer arc water ratio from 1.0 to 0.74 mitigates transverse thermal gradients. In addition, shutting off selected nozzles in the later stage of secondary cooling at medium and low casting speeds increases the slab corner temperature in the straightening zone by approximately 50 °C, thereby avoiding brittle temperature ranges. Overall, the proposed multi-dimensional uniform cooling strategy reduces temperature fluctuations and significantly improves slab quality, demonstrating strong potential for industrial application. Full article

Many studies have examined normal impacts on glass, but data on oblique impacts are limited, and, in particular, there is very limited experimental data on oblique impacts at various angles under consistent experimental conditions. Therefore, this study investigated fracture patterns of 5 mm thick low-emissivity (low-e) glass impacted by a 10 mm steel ball at velocities of 40 to 50 m/s at various oblique impact angles from 0° to 80°. Results showed that fracture patterns varied clearly with impact angle. Truncated cone fractures occurred in all specimens at 0° to 60°, while three of six specimens did not fracture at 80° because the normal energy dropped to below damage limit energy. Damage parameters normalized by kinetic energy showed that C_max/KE and C_min/KE remained stable at 5.7–6.4 and 4.9–5.3 mm/J from 0° to 45°, but dropped sharply to 0.7 and 0.6 mm/J at 80°. The aspect ratio of cone cracks remained relatively constant (1.2–1.3) regardless of oblique impact angle, while the aspect ratio of perforated holes increased from 1.0 (0°) to 1.6 (60°) before decreasing at 80°. Steel ball size comparison confirmed that normalized damage patterns are not significantly affected by projectile size variations. Mechanism-based analysis revealed that cone cracks and perforated holes are governed by fundamentally different physical processes. Cone cracks form through axisymmetric stress fields following Hertzian contact theory, showing limited angular sensitivity (15.4% maximum eccentricity change). In contrast, perforated holes result from trajectory-dependent mechanical penetration, exhibiting extreme angular sensitivity with 338.9% eccentricity increase from 0° to 60°. This 22-fold difference demonstrates a dual damage mechanism framework that explains the pronounced angular dependence of hole geometry versus the relative stability of cone crack patterns. These findings provide essential data for forensic glass analysis and impact-resistant glazing design, while the dual mechanism concept offers new insights into angle-dependent fracture behavior of brittle materials. Full article

Accurate assessment of sleep architecture is critical for diagnosing and managing sleep disorders, which significantly impact global health and well-being. While polysomnography (PSG) remains the clinical gold standard, its inherent intrusiveness, high cost, and logistical complexity limit its utility for routine or home-based monitoring. Recent advances highlight that subtle variations in respiratory dynamics, such as respiratory rate and cycle regularity, exhibit meaningful correlations with distinct sleep stages and could serve as valuable non-invasive biomarkers. In this work, we propose a framework for estimating sleep stage distribution—specifically Wake, Light (N1+N2), Deep (N3), and REM—based on respiratory audio captured over a single sleep episode. The framework comprises three principal components: (1) a segmentation module that identifies distinct respiratory cycles in respiratory sounds using a fine-tuned Transformer-based architecture; (2) a feature extraction module that derives a suite of statistical, spectral, and distributional descriptors from these segmented respiratory patterns; and (3) stage-specific regression models that predict the proportion of time spent in each sleep stage. Experiments on the public PSG-Audio dataset (287 subjects; mean 5.3 h per subject), using subject-wise cross-validation, demonstrate the efficacy of the proposed approach. The segmentation model achieved lower RMSE and MAE in predicting respiratory rate and cycle duration, outperforming classical signal-processing baselines. For sleep stage proportion prediction, the proposed method yielded favorable RMSE and MAE across all stages, with the TabPFN model consistently delivering the best results. By quantifying interpretable respiratory features and intentionally avoiding black-box end-to-end modeling, our system may support transparent, contact-free sleep monitoring using passive audio. Full article

In the context of digital school development, the leadership practices of school leadership teams play a significant role. If leadership teams want to enact leadership practices effectively, they require strong connections to the entire teaching staff as well as close contact with other key actors in the digital process. Since little is known about these connection patterns of school leadership teams, this study aims to uncover them. The aim is to provide practical advice to school administrators and schools regarding digital school development, and to derive concrete recommendations for action concerning their relationships and management. To this end, we examined the social networks of the teaching staff of 13 German secondary schools (N = 817 teachers) by asking all the teachers to complete a questionnaire about their contacts in relation to digital school development. We conducted a social network analysis and extracted various network metrics pertaining to the school leadership teams of these institutions, considering not only their integration within the overall network but also their connections with a pivotal stakeholder: the digital coordinator. To contextualize our findings, we compared the network metrics of the two different professional target groups using t-tests. The results reveal significant variability in the connection patterns of school leadership teams across different schools. Furthermore, our analysis indicates that digital coordinators consistently exhibit higher levels of connectedness within the realm of digital school development than the members of the school leadership teams. These findings highlight the importance of close collaboration between school leadership teams and the digital coordinator in order to advance digital school development. It is also suggested that school leadership teams should consider delegating more responsibilities to the digital coordinator, particularly those necessitating close collaboration with the teaching staff. Full article

In this paper, the evaluation of the mechanical performance of novel, designed topologically optimized shin pads with advanced materials will be conducted with the aid of Finite Element Analysis (FEA) to assess the endurance of the final structure on impact phenomena extracted from actual real-life data acquired from contact sports. The main focus of the developed prototype is to have high-enough energy absorption capabilities and vibration isolation properties, crucial for the development of trustworthy protective equipment. The insertion of advanced materials with controlled weight fractions and lattice geometries aims to strategically improve those properties and provide tailored characteristics similar to the actual human skeleton. The final design is expected to be used as standalone protective equipment for athletes or as a protective shield for the development of human lower limb prosthetics. In this context, computational investigation of the dynamic mechanical response was conducted by replicating a real-life phenomenon of the impact during a contact sport in a median condition of a stud kick impact and an extreme case scenario to assess the dynamic response under shock-absorption conditions and the final design’s structural integrity by taking into consideration the injury prevention capabilities. The results demonstrate that the proposed lattice geometries positively influence the injury prevention capabilities by converting a severe injury to light one, especially in the gyroid structure where the prototype presented a unified pattern of stress distribution and a higher reduction in the transmitted force. The incorporation of the PA-12 matrix reinforced with the reused ground tire rubber results in a structure with high enough overall strength and crucial modifications on the absorption and damping capabilities vital for the integrity under dynamic conditions. Full article

Photogrammetry offers a non-contact and efficient alternative for monitoring structural deformation and is particularly suited to large or complex surfaces such as masonry walls. This study proposes a spatio-temporal photogrammetric refinement framework that enhances the accuracy of three-dimensional (3D) deformation and strain analysis by integrating advanced filtering techniques into markerless image-based measurement workflows. A hybrid methodology was developed using natural image features extracted using the Speeded-Up Robust Features algorithm and refined through a three-stage filtering process: median absolute deviation filtering, Gaussian smoothing, and representative point selection. These techniques significantly mitigated the influence of noise and outliers on deformation and strain analysis. Comparative experiments using both manually placed targets and automatically extracted feature points on a full-scale masonry wall under destructive loading demonstrated that the proposed spatio-temporal filtering effectively improves the consistency of displacement and strain fields, achieving results comparable to traditional marker-based methods. Validation against laser rangefinder measurements confirmed sub-millimeter accuracy in displacement estimates. Additionally, strain analysis based on filtered data captured crack evolution patterns and spatial deformation behavior. Therefore, integrating photogrammetric 3D point tracking with spatio-temporal refinement provides a practical, accurate, and scalable approach to monitor structural deformation in civil engineering applications. Full article

In order to tackle the issues of poor mobility and unstable traction of electric vehicles on sandy landscapes, this research develops a high-accuracy numerical model for wheel–sand interaction relying on the Discrete Element Method (DEM). An innovative parameter calibration procedure is proposed herein, which optimizes the sand contact parameters. This reduces the error between the simulated and measured angles of repose to merely 1.2% and substantially improves the model’s reliability. The model was then used to systematically compare the performance of a 205/55 R16 slick tire with a treaded tire on sand. Simulations demonstrate that at a 30% slip ratio, the treaded tire exhibited significantly higher traction and greater sinkage than the slick tire. This indicates that tread patterns enhance traction mechanically by increasing the contact area and promoting shear deformation of the sand. The trends of traction with slip ratio and the corresponding sand flow patterns showed excellent agreement with experimental observations, which validated the simulation approach. This research provides an efficient and accurate tool for evaluating tire-sand interaction, providing critical support for the design and control of electric vehicles on complex terrains. Full article

Immunocompromised outpatients, including people living with HIV/AIDS (PLWH), diabetes, cancer, and organ transplant recipients, are at high risk of antimicrobial resistance (AMR) due to their weakened immune systems and use of immunosuppressive therapies. The high prevalence of prophylactic and therapeutic antibiotic use in this vulnerable population, coupled with frequent contact with healthcare facilities and limited outpatient antimicrobial resistance surveillance systems, contributes to the increase in antimicrobial resistance. The majority of available data pertains to inpatients, and there is a lack of comprehensive outpatient information on pathogen distribution, resistance patterns, and diagnostic challenges. Moreover, nonspecific clinical presentations, diminished inflammatory responses, and limitations of traditional diagnostic methods complicate infection diagnosis in this population. Increasing resistance surveillance, developing rapid diagnostic tools, and implementing accurate and personalized approaches are key strategies to reduce the burden of disease, mortality, and healthcare costs in the immunocompromised outpatient population. This study was designed as a narrative review based on a comprehensive search of major databases and guidelines. It aims to examine the available evidence and address the challenges associated with AMR in immunocompromised outpatients. Full article

Urban industrial complexes have been expanding worldwide, reducing the spatial separation between agricultural, residential, and industrial zones, particularly in developing nations. Urban road dust contamination, a sensitive indicator of urban environmental quality, primarily originates in urbanization and industrialization. Its detrimental impacts on human health arise not only from particulate matter itself but also from toxic and harmful substances embedded within dust particles. Toxic metals in road dust can pose health risks through inhalation, ingestion and contact. To investigate the seasonal patterns, bioaccessibility levels and the potential human health risks linked to toxic metals (Cadmium (Cd), Nickel (Ni), Arsenic (As), Lead (Pb), Zinc (Zn), Copper (Cu), and Chromium (Cr)), 34 dust samples were collected from key roads in proximity to representative industrial facilities in Wuhan’s Qingshan District. The study found that the concentrations of Cd, Pb, and Cu in road dust were within the limits set by the national standard (GB 15618-2018), while Ni and As were not. Seasonally, Ni, As, Pb, Zn, and Cr exhibited higher concentrations during the summer than in other seasons, whereas Cd levels were lowest in spring and highest in autumn, the opposite of Cu. According to the Simplified Bioaccessibility Extraction Test (SBET), the average bioaccessibility rates of toxic metals were Cd > Zn > Cu > Ni > Cr > As > Pb. An improved health risk assessment model was developed, integrating metal enrichment, bioaccessibility, and parameter uncertainty. Results indicated that Cd, Ni, Zn, Cu, As, and Cr posed no significant non-carcinogenic risk. However, for children, the carcinogenic risks of Cd and As were relatively high, identifying them as priority control metals. Therefore, it is recommended to periodically monitor As and Cd and regulate their potential emission sources, especially in winter and spring. Full article

Intimate partner violence (IPV) has far-reaching health and social consequences, particularly for survivors experiencing polyvictimization—multiple forms of IPV such as physical, emotional, and sexual abuse. This study examined help-seeking behaviors and the perceived helpfulness of formal support sources (police, medical professionals, and psychologists) among a nationally representative sample of 2387 IPV survivors drawn from the 2010 National Intimate Partner and Sexual Violence Survey (NISVS) in the United States. Latent class analysis identified three distinct polyvictimization profiles: Coercive Control and Psychological Aggression (CCPA), Psychological and Physical Violence (PPV), and Multiple Violence (MV). Survivors’ patterns of formal help-seeking varied significantly by gender, sexual orientation, socioeconomic status, and type of victimization. Psychologists were the most commonly contacted and perceived as the most helpful overall, though disparities emerged. Female survivors and those with less severe victimization were more likely to rate support as helpful, whereas male and sexual/gender minority (SGM) survivors, particularly those facing severe or multiple forms of violence, were less likely to find formal sources helpful—especially law enforcement. These findings highlight the need for more inclusive, culturally competent, and trauma-informed services tailored to the diverse experiences of IPV survivors. Full article

In this study, the behavior of the spherical bearing component of the L-100 bridge part (AlfaTech LLC, Perm, Russia) is considered within the framework of a finite element model. The influence of the pattern of the coupling of the antifriction interlayer with the lower steel plate on the operation of the part is examined in terms of ideal contact, full adhesion, and frictional contact. The thickness of the antifriction interlayer varied from 4 to 12 mm. The dependencies of the contact parameters and the stress–strain state on the thickness were determined. Structurally modified polytetrafluoroethylene (PTFE) without AR-200 fillers was considered the material of the antifriction interlayer. The gradual refinement of the behavioral model of the antifriction material to account for structural and relaxation transitions was carried based on a wide range of experimental studies. The elastic–plastic and primary viscoelastic models of material behavior were constructed based on a series of homogeneous deformed-state experiments. The viscoelastic model of material behavior was refined using data from dynamic mechanical analysis over a wide temperature range [−40; +80] °C. In the first approximation, a model of the deformation theory of plasticity with linear elastic volumetric compressibility was identified. As a second approximation, a viscoelasticity model for the Maxwell body was constructed using Prony series. It was established that the viscoelastic model of the material allows for obtaining data on the behavior of the part with an error of no more than 15%. The numerical analog of the construction in an axisymmetric formulation can be used for the predictive analysis of the behavior of the bearing, including when changing the geometric configuration. Recommendations for the numerical modeling of the behavior of antifriction layer materials and the coupling pattern of the bearing elements are given in this work. A spherical bearing with an antifriction interlayer made of Arflon series material is considered for the first time. Full article

This article presents a principled framework for selecting and tuning classical computer vision algorithms in the context of optical displacement sensing. By isolating key factors that affect algorithm behavior—such as feed window size and motion step size—the study seeks to move beyond intuition-based practices and provide rigorous, repeatable performance evaluations. Computer vision-based optical odometry sensors offer non-contact, high-precision measurement capabilities essential for modern metrology and robotics applications. This paper presents a systematic comparative analysis of three classical tracking algorithms—phase correlation, template matching, and optical flow—for 2D surface displacement measurement using synthetic image sequences with subpixel-accurate ground truth. A virtual camera system generates controlled test conditions using a multi-circle trajectory pattern, enabling systematic evaluation of tracking performance using 400 × 400 and 200 × 200 pixel feed windows. The systematic characterization enables informed algorithm selection based on specific application requirements rather than empirical trial-and-error approaches. Full article