Search Results (1,528)

Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well acknowledged, but little work addresses what design or interactions techniques developers can employ or build into experiences to work around these limitations. We conducted a scoping literature review, with the aim of mapping the current landscape of design principles and interaction techniques employed in near-field AR environments. We searched for literature published between 2016 and 2025 across major databases, including the ACM Digital Library and IEEE Xplore. Studies were included if they explicitly employed design or interaction techniques with a commercially available HMD for near-field AR experiences. A total of 780 articles were returned by the search, but just 7 articles met the inclusion criteria. Our review identifies key themes around how existing techniques are employed and the two competing goals of AR experiences, and we highlight the importance of embodiment in interaction efficacy. We present directions for future research based on and justified by our review. The findings offer a comprehensive overview for researchers, designers, and developers aiming to create more intuitive, effective, and context-aware near-field AR experiences. This review also provides a foundation for future research by outlining underexplored areas and recommending research directions for near-field AR interaction design. Full article

As economically important sympatric species in the Northwest Pacific, the Japanese sardine (Sardinops melanostictus) and Chub mackerel (Scomber japonicus) exhibit significant biological interactions. Understanding the impact of interspecies competition on their habitat dynamics can provide crucial insights for the sustainable development and management of these interconnected species resources. This study utilizes fisheries data of S. melanostictus and S. japonicus from the Northwest Pacific, collected from June to November between 2017 and 2020. We integrated various environmental parameters, including temperature at different depths (0, 50, 100, 150, and 200 m), eddy kinetic energy (EKE), sea surface height (SSH), chlorophyll-a concentration (Chl-a), and the oceanic Niño index (ONI), to construct interspecific competition species distribution model (icSDM) for both species. We validated these models by overlaying the predicted habitats with fisheries data from 2021 and performing cross-validation to assess the models’ reliability. Furthermore, we conducted correlation analyses of the habitats of these two species to evaluate the impact of interspecies relationships on their habitat dynamics. The results indicate that, compared to single-species habitat models, the interspecific competition species distribution model (icSDM) for these two species exhibit a significantly higher explanatory power, with R² values increasing by up to 0.29; interspecific competition significantly influences the habitat dynamics of S. melanostictus and S. japonicus, strengthening the correlation between their habitat changes. This relationship exhibits a positive correlation at specific stages, with the highest correlations observed in June, July, and October, at 0.81, 0.80, and 0.88, respectively; interspecific competition also demonstrates stage-specific differences in its impact on the habitat dynamics of S. melanostictus and S. japonicus, with the most pronounced differences occurring in August and November. Compared to S. melanostictus, interspecific competition is more beneficial for the expansion of the optimal habitat (HIS ≥ 0.6) for S. japonicus and, to some extent, inhibits the habitat expansion of S. melanostictus. The variation in migratory routes and predatory interactions (with larger individuals of S. japonicus preying on smaller individuals of S. melanostictus) likely constitutes the primary factors contributing to these observed differences. Full article

Accurate delineation of within-field management zones (MZs) is essential for implementing precision agriculture, particularly in spatially heterogeneous environments. This study evaluates the spatiotemporal consistency and practical value of MZs derived from three complementary data sources: electromagnetic conductivity (EM38-MK2), basic soil chemical properties (pH, humus, P₂O₅, K₂O, nitrogen), and vegetation/surface indices (NDVI, SAVI, LCI, BSI) derived from Sentinel-2 imagery. Using kriging, fuzzy k-means clustering, percentile-based classification, and Weighted Overlay Analysis (WOA), MZs were generated for a five-year period (2018–2022), with 2–8 zone classes. Stability and agreement were assessed using the Cohen Kappa, Jaccard, and Dice coefficients on systematic grid samples. Results showed that EM38-MK2 and humus-weighted BSP data produced the most consistent zones (Kappa > 0.90). Sentinel-2 indices demonstrated strong alignment with subsurface data (r > 0.85), offering a low-cost alternative in data-scarce settings. Optimal zoning was achieved with 3–4 classes, balancing spatial coherence and interpretability. These findings underscore the importance of multi-source data integration for robust and scalable MZ delineation and offer actionable guidelines for both data-rich and resource-limited farming systems. This approach promotes sustainable agriculture by improving input efficiency and allowing for targeted, site-specific field management. Full article

Small towns in mountainous regions face significant challenges in formulating effective landscape zoning strategies due to pronounced landscape fragmentation, which is driven by both the dominance of large-scale forest resources and the lack of coordination between administrative planning departments. To tackle this problem, this study focused on Yuqian, a quintessential small mountainous town in Hangzhou, Zhejiang Province. The town’s layout was divided into a grid network measuring 70 m × 70 m. A two-step cluster process was employed using ArcGIS and SPSS software to analyze five landscape variables: altitude, slope, land use, heritage density, and visual visibility. Further, eCognition software’s semi-automated segmentation technique, complemented by manual adjustments, helped delineate landscape character types and areas. The overlay analysis integrated these areas with administrative village units, identifying four landscape character types across 35 character areas, which were recategorized into four planning and management zones: urban comprehensive service areas, agricultural and cultural tourism development areas, industrial development growth areas, and mountain forest ecological conservation areas. This result optimizes the current zoning types. These zones closely match governmental sustainable development zoning requirements. Based on these findings, we propose integrated landscape management and conservation strategies, including the cautious expansion of urban areas, leveraging agricultural and cultural tourism, ensuring industrial activities do not impact the natural and village environment adversely, and prioritizing ecological conservation in sensitive areas. This approach integrates spatial and administrative dimensions to enhance landscape connectivity and resource sustainability, providing key guidance for small town development in mountainous regions with unique environmental and cultural contexts. Full article

This study applies the Weighted Overlay Analysis (WOA) method integrated with GIS to assess landslide susceptibility along Al Figrah Road in Al-Madinah Al-Munawarah, western Saudi Arabia. Seven key conditioning factors, elevation, slope, aspect, drainage density, lithology, soil type, and precipitation were integrated using high-resolution remote sensing data and expert-assigned weights. The output susceptibility map categorized the region into three zones: low (93.5 million m²), moderate (271.2 million m²), and high risk (33.1 million m²). Approximately 29% of the road corridor lies within the low-risk zone, 48% in the moderate zone, and 23% in the high-risk zone. Ten critical sites with potential landslide activity were detected along the road, correlating well with the high-risk zones on the map. Structural weaknesses in the area, such as faults, joints, foliation planes, and shear zones in both igneous and metamorphic rock units, were key contributors to slope instability. The findings offer practical guidance for infrastructure planning and geohazard mitigation in arid, mountainous environments and demonstrate the applicability of WOA in data-scarce regions. Full article

Traditional acupuncture relies on the precise selection of acupuncture points to adjust Qi flow along meridians. Traditionally, acupuncture points are localized using cun (or body-relative cun) as a proportional measurement. However, locating specific points can be challenging, even for experienced practitioners. This study aims to enhance the accuracy and efficiency of acupuncture point localization by introducing an augmented reality (AR) navigation system utilizing AR glasses (Magic Leap One). The system employs a Six-Point Landmark-Based AR Registration method to overlay an acupuncture point model onto a patient’s head without the need for external markers. Methods included testing with traditional Chinese medicine students, measuring positional errors, and evaluating stability. Results demonstrated an average error of 5.01 ± 2.64 mm, which is well within the therapeutic range of 2 cun (about 5 cm), with minimal drift during stability tests. This AR system provides an accurate and intuitive tool for practitioners and learners, reducing variability in acupuncture point selection and offering promise for broader clinical applications. Full article

Objectives: Torus mandibularis (TM) is a benign bony exostosis on the lingual surface of the mandible, typically developing from the third decade of life with slow progression; its etiology remains unclear. As TM excision causes no functional or aesthetic disadvantages, its use as autologous bone graft material (e.g., for pre-implant or sinus lift augmentation) has been suggested. In this study, we investigate the prevalence and expression of TM in a southern German population with regard to age and gender. Additionally, we examine whether TM undergoes dynamic changes over time, with the hypothesis that TM may show temporal growth. Material and Methods: A retrospective analysis of CBCT scans from 210 randomly selected patients (105 males, 105 females) was performed. Patients were divided into three age groups (≤40, 41–60, ≥61 years; 70 per group), and TM was measured using OsiriX MD. For the longitudinal study, 146 CBCTs from 73 patients were compared over intervals of 2–9 years. Surface changes were assessed via 3D overlay using GOM Inspect. Results: TM was found in 30.5% of patients, and its prevalence was significantly higher in males (38%) than females (23%), with no age-related differences identified. Most TMs measured <2 mm (n = 51); only five exceeded this size. No dynamic growth was observed over time. Conclusion and Clinical Implications: TM is a common anatomical variant, more frequently detected through 3D imaging than clinical examination. In most cases, size remains minimal (<2 mm), limiting its clinical use as augmentation material in rare individual cases. Full article

With the growing adoption of 3D stacked memory structures, precise alignment and overlay control have become critical for multi-layer overlay accuracy. The metrology accuracy and stability of alignment marks are crucial to ensuring optimal alignment and overlay performance. This study systematically investigates the contributions of two key alignment parameters—Wafer Quality (WQ) and Alignment Position Deviation (APD)—to the alignment model residue in 3D structures. Through experimental and simulation approaches, we analyze the interplay between WQ, APD and overlay performance. Results reveal that APD exhibits a stronger correlation with uncorrectable model residue, particularly under global process variations such as etch non-uniformity. Furthermore, APD sensitivity varies directionally (X/Y direction marks) and spatially (wafer edge versus center), highlighting the need for targeted mark designs in process-sensitive zones. These findings provide actionable insights for optimizing alignment strategies, mark designs and process monitoring throughout R&D, technology development and high-volume manufacturing phases. Full article

This study proposes a deep learning-based method to improve overlay alignment precision in laser direct writing systems. Alignment errors arise from multiple sources in nanoscale processes, including optical aberrations, mechanical drift, and fiducial mark imperfections. A significant portion of the residual alignment error stems from the interpretation of mark coordinates by the vision system and algorithms. Here, we developed a convolutional neural network (CNN) model to predict the coordinates calculation error of 66,000 sets of computer-generated defective crosshair marks (simulating real fiducial mark imperfections). We compared 14 neural network architectures (8 CNN variants and 6 feedforward neural network (FNN) configurations) and found a well-performing, simple CNN structure achieving a mean squared error (MSE) of 0.0011 on the training sets and 0.0016 on the validation sets, demonstrating 90% error reduction compared to the FNN structure. Experimental results on test datasets showed the CNN’s capability to maintain prediction errors below 100 nm in both X/Y coordinates, significantly outperforming traditional FNN approaches. The proposed method’s success stems from the CNN’s inherent advantages in local feature extraction and translation invariance, combined with a simplified network architecture that prevents overfitting while maintaining computational efficiency. This breakthrough establishes a new paradigm for precision enhancement in micro–nano optical device fabrication. Full article

This paper proposes a multi-hop peer-to-peer (P2P) video streaming architecture designed to support dynamic, conversation-aware communication. The primary contribution is a decentralized system built on WebRTC that eliminates reliance on a central media server by employing super node aggregation. In this architecture, video streams from multiple peer nodes are dynamically routed through a group of super nodes, enabling real-time reconfiguration of the network topology in response to conversational changes. To support this dynamic behavior, the system leverages WebRTC data channels for control signaling and overlay restructuring, allowing efficient dissemination of topology updates and coordination messages among peers. A key focus of this study is the rapid and efficient reallocation of network resources immediately following conversational events, ensuring that the streaming overlay remains aligned with ongoing interaction patterns. While the automatic detection of such events is beyond the scope of this work, we assume that external triggers are available to initiate topology updates. To validate the effectiveness of the proposed system, we construct a simulation environment using Docker containers and evaluate its streaming performance under dynamic network conditions. The results demonstrate the system’s applicability to adaptive, naturalistic communication scenarios. Finally, we discuss future directions, including the seamless integration of external trigger sources and enhanced support for flexible, context-sensitive interaction frameworks. Full article

Currently, numerous conventional airport runways suffer from cracking distresses and cannot meet their structural and functional requirements. To address the urgent demand for rapid and durable maintenance of airport runways, this study investigates the material optimization and curing behavior of cold-mix epoxy asphalt (CEA) for non-disruptive overlays. Eight commercial CEAs were examined through tensile and overlay tests to evaluate their strength, toughness, and reflective cracking resistance. Two high-performing formulations (CEA 1 and CEA 8) were selected for further curing characterization using differential scanning calorimetry (DSC) tests, and the non-isothermal curing kinetics were analyzed with different contents of Component C. The results reveal that CEA 1 and CEA 8 were selected as promising formulations with superior toughness and reflective cracking resistance across a wide temperature range. DSC-based curing kinetic analysis shows that the curing reactions follow an autocatalytic mechanism, and activation energy decreases with conversion, confirming a self-accelerating process of CEA. The addition of Component C effectively modified the curing behavior, and CEA 8 with 30% Component C reduced curing time by 60%, enabling traffic reopening within half a day. The curing times were accurately predicted for each type of CEA using curing kinetic models based on autocatalytic and iso-conversional approaches. These findings will provide theoretical and practical guidance for high-performance airport runway overlays, supporting rapid repair, extended service life, and environmental sustainability. Full article

Background/Objectives: This paper presents a medical image analysis application designed to facilitate advanced edge detection and fuzzy processing techniques within an intuitive, modular graphical user interface. Methods: Key functionalities include classical edge detection, Ant Colony Optimization (ACO)-based edge extraction, and fuzzy edge generation, which offer improved boundary representation in images where uncertainty and soft transitions are prevalent. Results: One of the main novelties in contrast to the initial innovative Medical Image Analyzer, iMIA, is the fact that the system includes fuzzy C-means clustering to support tissue classification and unsupervised segmentation based on pixel intensity distribution. The application also features an interactive zooming and panning module with the option to overlay edge detection results. As another novelty, fuzzy performance metrics were added, including fuzzy false negatives, fuzzy false positives, fuzzy true positives, and the fuzzy index, offering a more comprehensive and uncertainty-aware evaluation of edge detection accuracy. Conclusions: The application executable file is provided at no cost for the purposes of evaluation and testing. Full article

Antibiotic resistance is one of the most significant public health issues today. As a consequence, there is an urgent need for novel classes of antibiotics. This necessitates the development of highly efficient screening methods for the rapid identification of antibiotic-producing bacteria. Here, we describe a new method for high-throughput screening of antimicrobial compounds (AMC) producing halophilic bacteria. Our methodology used a newly designed 3D-printed Petri plate replicator used for drop deposition and colony replication. We employed this device in combination with a modified agar overlay assay to screen more than 7400 bacterial colonies. A total of 54 potential AMC producers were discovered at a success rate of 0.7%. Although 40% of them lost their antibacterial activity during the secondary screening, 22 strains retained inhibitory activity and were able to suppress the growth of one or more safe relatives of the ESKAPE group pathogens. The ethyl acetate extract from the most potent strain, Virgibacillus salarius POTR191, demonstrated moderate antibacterial activity against Enterococcus faecalis, Acinetobacter baumanii, and Staphylococcus epidermidis with minimal inhibitory concentrations of 128 μg/mL, 128 μg/mL, and 512 μg/mL, respectively. We propose that our replica plate assay could be used for target-based antimicrobial screening of various extremophilic bacteria. Full article

The rising popularity of ecotourism on the Tibetan Plateau has intensified the tension between wildlife conservation and economic development. Conventional wildlife displays often fail to achieve high-fidelity, non-invasive representations of animal morphology and typically lack immersive, interactive features, limiting public engagement in ecological protection. To address these limitations, this study presents a fur simulation algorithm based on the Texture Procedural Overlay Technique (TPOT), integrated with Augmented Reality (AR) technology, focusing on the endangered white-lipped deer in the Sanjiangyuan region. The proposed TPOT-based algorithm enhances the visual realism of fur through multi-layered procedural texturing and physical property fusion. Combined with an AR-driven interactive framework, it seamlessly integrates high-resolution 3D models into real-world environments, significantly improving user immersion and engagement. Comparative experiments demonstrate that the approach surpasses traditional static display fidelity and animation rendering efficiency methods. User feedback further validates its effectiveness for scientific research and environmental education. This work introduces an innovative technological solution for wildlife conservation on the Tibetan Plateau and provides a practical reference for applying digital technologies in ecotourism. Full article

A system of field protective forest belts (FPFBs) was created in the middle of the 20th century in Southern Dobrudzha (Northern Bulgaria) to reduce wind erosion, improve soil moisture storage, and increase agricultural crop yields. Since 2020, prolonged climatic drought during growing seasons and the advanced age of trees have adversely impacted the health status of planted species and resulted in the decline and dieback of the FPFBs. Physiologically stressed trees have become less able to resist pests, such as insects and diseases. In this work, an original new methodology for the integrated assessment of the condition of FPFBs and their protective capacity is presented. The presented methods include the assessment of structural and functional characteristics, as well as the health status of the dominant tree species. Five indicators were identified that, to the greatest extent, present the ability of forest belts to perform their protective functions. Each indicator was evaluated separately, and then an overlay analysis was applied to generate an integrated assessment of the condition of individual forest belts. Three groups of FPFBs were differentiated according to their condition: in good condition, in moderate condition, and in bad condition. The methodology was successfully tested in Southern Dobrudzha, but it could be applied to other regions in Bulgaria where FPFBs were planted, regardless of their location, composition, origin, and age. This methodological approach could be transferred to other countries after adapting to their geo-ecological and agroforest specifics. The methodological approach is an informative and useful tool to support decision-making about FPFB management, as well as the proactive planning of necessary forestry activities for the reconstruction of degraded belts. Full article