Search Results (313)

The performance of the human eye is limited not only by optical factors but also capabilities of signal processing. The maximum spatial frequency that can be reliably processed depends on the sampling rate. If this frequency is exceeded, spatial aliasing occurs. In this study, we investigate the optimum amount of defocus and spherical aberration needed to avoid spatial aliasing. Measurements are carried out using a simple model eye with the optical and geometrical parameters close to those of a living human eye. A checkerboard pattern with the spatial frequency of 60 cycles/degree is used as a stimulus. A deformable mirror was used to control the amount of defocus and spherical aberration from 0 µm to 0.50 µm in steps of 0.05 µm. If the amount of aberrations is low, fringes of aliased signals are visible along the direction 35.5 degrees relative to the vertical edge of the image. This direction is close to the diagonal direction along which the sampling rate is the lowest. When the amount of aberrations reaches 0.45 µm, spatial aliasing is not observed. The results suggest that low amount of ocular aberrations is desired. Full article

Structured-light 3D reconstruction is an active measurement technique that extracts spatial geometric information of objects by projecting fringe patterns and analyzing their distortions. It has been widely applied in industrial inspection, cultural heritage digitization, virtual reality, and other related fields. This review presents a comprehensive analysis of mainstream fringe-based reconstruction methods, including Fringe Projection Profilometry (FPP) for diffuse surfaces and Phase Measuring Deflectometry (PMD) for specular surfaces. While existing reviews typically focus on individual techniques or specific applications, they often lack a systematic comparison between these two major approaches. In particular, the influence of different projection schemes such as Digital Light Processing (DLP) and MEMS scanning mirror–based laser scanning on system performance has not yet been fully clarified. To fill this gap, the review analyzes and compares FPP and PMD with respect to measurement principles, system implementation, calibration and modeling strategies, error control mechanisms, and integration with deep learning methods. Special focus is placed on the potential of MEMS projection technology in achieving lightweight and high-dynamic-range measurement scenarios, as well as the emerging role of deep learning in enhancing phase retrieval and 3D reconstruction accuracy. This review concludes by identifying key technical challenges and offering insights into future research directions in system modeling, intelligent reconstruction, and comprehensive performance evaluation. Full article

Long bone fractures are breaks or cracks in a long bone of the body typically caused by trauma like a fall, sport injury, accidents etc. This study investigates the effectiveness of experimental methods for fast and safe healing of long bone fractures in humans, highlighting both their advantages and disadvantages, respectively finding the most effective and safe methods for evaluating the types of fixators that can be used in the consolidation of fractured long bones. As for the preliminary data, numerical methods and applied mathematics were used to address this problem. After collecting of preliminary data there were performed a series of experimental analysis as follows: Electrical Strain Gauges (ESGs); the Moiré Fringes method; Photo-Elasticity, with the particular technique thereof, the so-called Photo-Stress method; Holographic Interferometry (HI); Speckle Pattern Interferometry (ESPI) and Shearography; and Video Image Correlation (VIC), which is also called Digital Image Correlation (DIC). By analyzing different methods, the following two methods resulted to be widely applicable, namely, ESG and DIC/VIC. The findings highlight the net advantages regarding the objective choice of these types of fixators, thereby contributing to a possible extension of these approaches for the benefit of medical surgical practice Full article

In recent years, the rapid expansion of urban rail transit has significantly improved travel efficiency, yet it has also exacerbated spatial inequality in service coverage. Accessibility, as a fundamental metric for evaluating the equity of service distribution, remains limited by three major shortcomings in current assessment methods: the neglect of actual road network characteristics, reliance on a single static scale, and the absence of quantitative mechanisms to assess accessibility equity. These deficiencies hinder a comprehensive understanding of how equity evolves with the spatiotemporal dynamics of rail systems. To address the aforementioned issues, this study proposes an innovative spatiotemporally dynamic and multi-scale analytical framework for evaluating urban rail accessibility and its equity implications. Specifically, we develop a network-based buffer decay model to refine service population estimation by incorporating realistic walking paths, capturing both distance decay and road network constraints. The framework integrates multiple spatial analytical techniques, including the Gini coefficient, Lorenz curve, global and local spatial autocorrelation, center-of-gravity shift, and standard deviation ellipse, to quantitatively assess the equity and evolutionary patterns of accessibility across multiple spatial scales. Taking the central urban area of Hangzhou as a case study, this research investigates the spatiotemporal patterns and equity changes in metro station accessibility in 2019 and 2023. The results indicate that the expansion of the metro network has partially improved overall accessibility equity: the Gini coefficient at the TAZ (Traffic Analysis Zone) scale decreased from 0.56 to 0.425. Nevertheless, significant inequality remains at finer spatial resolutions (grid-level Gini coefficient = 0.404). In terms of spatial pattern, the core area (e.g., Wulin Square) forms a ‘high-high’ accessibility agglomeration area, while the urban fringe area (e.g., northern Yuhang) presents a ‘low-low’ agglomeration, and the problem of local ‘accessibility depression’ still exists. Additionally, the accessibility centroid has consistently shifted northwestward, and the long axis of the standard deviation ellipse has rotated from an east–west to a northwest-southeast orientation, indicating a growing spatial polarization between core and peripheral zones. The findings suggest that improving equity in urban rail accessibility cannot rely solely on expanding network size; rather, it requires coordinated strategies involving network structure optimization, branch line development, multimodal integration, and the construction of efficient transfer systems to promote more balanced and equitable spatial distribution of rail transit resources citywide. Full article

In recent years, the proliferation of social platforms has drastically transformed how individuals interact, organize, and share information. In this scenario, there has been an unprecedented increase in the scale and complexity of interactions and, at the same time, little to no research about certain fringe social platforms. In this paper, we present a multi-dimensional framework for characterizing nodes and hyperedges in social hypernetworks, with a focus on the understudied alt-right platform Scored.co. Our approach integrates the possibility of studying higher-order interactions, thanks to the hypernetwork representation, and various node features such as user activity, sentiment, and toxicity, with the aim of defining distinct user archetypes and understanding their roles within the network. Utilizing a comprehensive dataset from Scored.co, consisting of more than 4.4 M posts and 36.9 M comments, we analyze the dynamics of these archetypes over time and explore their interactions and influence within the community. We identify eight archetypes, with the largest group comprising over 15,000 users, and observe that 44% of interactions involve at least five participants, highlighting the importance of higher-order modeling. Furthermore, we find significant archetype transitions and stable yet locally dense interaction patterns, with users exposed to roughly 1000 unique peers on average. The framework’s versatility allows for detailed analysis of both individual user behaviors and broader social structures. Our findings highlight the importance of higher-order interactions and node features in understanding social dynamics, and offer new insights into the roles and behaviors that emerge in complex online environments. Full article

This study introduces a novel, low-cost, and non-invasive method for characterizing the surface profile of transparent objects using double digital fringe projection (DDFP). By projecting dual sinusoidal patterns that generate a Moiré effect and applying a frequency-domain Gaussian filter, the system isolates relevant data for accurate phase recovery through the isotropic quadrature transform (IQT). Experimental validation with plastic and acrylic samples confirms the method’s high spatial resolution and robustness against ambient noise. Unlike traditional systems, this technique avoids coherent light sources and complex hardware, improving its accessibility for academic and industrial use in transparent surface metrology. Full article

Interference lithography (IL) offers high throughput, excellent uniformity, and maskless patterning capabilities. Compared to other methods, IL enables large-area, cost-effective fabrication of periodic structures with subwavelength resolution, which is particularly valuable for sensing applications, enabling the development of more sensitive, high-resolution, and reliable sensors. This review provides a comprehensive analysis of IL from the perspective of optical field control. We first introduce the principles of interference field formation and summarize key system architectures, including Mach–Zehnder and Lloyd’s mirror configurations, as well as advanced schemes such as multi-beam interference and multi-step exposure for complex pattern generation. We then examine how wavefront engineering, polarization modulation, and phase stabilization influence pattern morphology, contrast, and large-area uniformity. To address dynamic drifts caused by environmental perturbations, both passive vibration isolation and active fringe-locking techniques are discussed. For fringe-locking systems, we review methods for drift monitoring, control algorithms, and feedback implementation. These developments enhance the capability of IL systems to deliver nanoscale accuracy under dynamic conditions, which is essential for stable and high-performance sensing. Looking ahead, IL is evolving into a versatile platform for sensor-oriented nanofabrication. By integrating physical modeling, precision optics, and real-time control, IL provides a robust foundation for advancing next-generation sensing technologies with higher sensitivity, resolution, and reliability. Full article

Laser Powder Bed Fusion (L-PBF) parts combine geometric freedom with process-induced rough surfaces that challenge residual-stress metrology. We evaluated the accuracy of the incremental hole-drilling (IHD) method with electronic speckle pattern interferometry (ESPI) by applying defined stresses via four-point bending to stress-relieved AlSi10Mg coupons, rather than measuring unknown process stresses. Flat specimens (2 mm, thin per ASTM E837) were analyzed on up-skin, side-skin, and CNC-milled surfaces; thin-specimen calibration coefficients were used. After a preliminary inter-specimen check (three specimens per surface; spread < 8 MPa), one representative specimen per surface was tested with three drill sites to assess intra-specimen uniformity. Measured IHD–ESPI stresses agreed best at 70 MPa: deviations were ~4.1% (up-skin), 6.0% (side-skin), and 6.24% (CNC-milled). At 10 MPa the relative errors increased (23.6%, 18.4%, and 1.40%), consistent with reduced ESPI signal-to-noise and fixture compliance in the low-stress regime. At 140 MPa, deviations rose again (21.1%, 14.3%, and 13.1%), reflecting operation near the ~60% Rp0.2 elastic limit of hole-drilling and potential local plasticity. Surface-dependent artifacts also mattered as follows: the side-skin required no coating and performed comparably to CNC-milled, whereas the up-skin’s roughness plus matting spray introduced fringe distortions and chip/coating debris near the hole. This controlled study indicates that IHD–ESPI can provide reliable results on L-PBF AlSi10Mg in the mid-stress range when surface preparation, coating, and rig compliance are carefully managed. Limitations include excluding down-skin surfaces and testing only one specimen per condition; thus, results should be generalized cautiously. Full article

Three-dimensional measurement of translucent objects using structured light techniques remained fundamentally challenging due to severe degradation of fringe patterns caused by subsurface scattering, which inevitably introduced phase errors and compromised measurement accuracy. Although deep learning had emerged as a powerful tool for fringe analysis, its practical implementation was hindered by the impractical requirement for large-scale labeled datasets, particularly in scattering-dominant measurement scenarios. To overcome these limitations, we developed a self-learning-based fringe domain conversion method inspired by image style transfer principles, where degraded and ideal fringe patterns were treated as distinct domains for cyclic translation. The proposed framework employed dual generators and discriminators to establish cycle-consistency constraints while incorporating both numerical intensity-based and physical phase-derived optimization targets, effectively suppressing phase errors and improving fringe modulation without requiring paired training data. Experimental validation demonstrated superior performance in reconstructing high-fidelity 3D morphology of translucent objects, establishing this approach as a robust solution for precision metrology of complex scattering media. Full article

Evaluation of socio-ecological vulnerability is crucial for sustainable management in mining cities. This study selected Xintai City, China, as a case and constructed a comprehensive vulnerability assessment framework based on 2010–2020 multi-source data. By integrating the Geodetector, spatial autocorrelation analysis, and ordered weighted averaging (OWA), we systematically explored the spatio-temporal patterns and driving mechanisms of socio-ecological vulnerability. The Theil index at the village level revealed finer spatial heterogeneity than large-scale analyses. The results show the following: (1) Socio-ecological vulnerability in Xintai City is generally moderate, with high-vulnerability areas concentrated in the urban center and former coal mining zones. Over the past decade, high—vulnerability levels in these areas have improved, whereas the urban-rural fringe has experienced a significant increase in vulnerability, primarily driven by industrial transfer and uneven resource allocation. (2) Geodetector analysis indicated a shift in dominant drivers from natural to socio-economic factors, with population density and construction land proportion surpassing natural conditions such as average annual rainfall by 2020. Additionally, mining land proportion, land use change, and the spatial distribution of social services played key roles in shaping vulnerability patterns, while ecological and public service factors showed weaker explanatory power. (3) Scenario simulation based on OWA demonstrated that an economic-priority pathway leads to the outward expansion of vulnerable areas into mountainous regions, while an ecological-priority approach promotes spatial contraction and optimization of vulnerability zones. These findings provide scientific guidance for identifying key vulnerable areas and formulating differentiated management strategies, offering reference value for the sustainable development of resource-exhausted mining cities. Full article

Rapid full-field surface topography measurement for large-scale wafers remains challenging due to limitations in speed, system complexity, and scalability. This work presents a interferometric system based on thin-film interference for high-precision wafer profiling. An optical flat serves as the reference surface, forming a parallel air-gap structure with the wafer under test. A large-aperture collimated beam is introduced via an off-axis parabolic mirror to generate high-contrast interference fringes across the entire field of view. Once the wafer is fully illuminated, topographic information is directly extracted from the fringe pattern. Comparative measurements with a commercial interferometer show relative deviations below $3\%$ in bow and warp, confirming the system’s accuracy and stability. With its simple optical layout, low cost, and robust performance, the proposed method shows strong potential for industrial applications in wafer inspection and online surface monitoring. Full article

Urban and peri-urban lakes are increasingly threatened by water quality degradation due to rising anthropogenic pressures and environmental variability. This study proposes an integrated framework that combines multi-source data and machine learning to estimate and monitor three key water quality parameters: turbidity, total dissolved solids (TDS), and biological oxygen demand (BOD). Field measurements from three lakes in West Bengal, India, Rabindra Sarovar, Mirikh Lake, and Hanuman Ghat Lake, were combined with Landsat-8 satellite imagery, meteorological data, and land use information. Three modeling scenarios were developed: (i) using only remote sensing indices, (ii) combining remote sensing indices with meteorological variables, and (iii) integrating remote sensing indices, meteorological data, and land use features. Principal component analysis (PCA) was used to reduce dimensionality and redundancy. Machine learning models, namely, XGBoost, Decision Tree, and Ridge Regression, were trained and evaluated using R² and RMSE (Root Mean Square Error) metrics. The third scenario outperformed the others, with Ridge Regression achieving the highest accuracy for BOD prediction (R² = 0.99). Spatiotemporal patterns revealed persistently high BOD levels along urban lake fringes and post-monsoon spikes in turbidity and TDS, especially in agriculturally influenced zones. These patterns were closely linked to land use practices, rainfall-driven runoff, and point-source pollution. This study underscores the effectiveness of remote sensing and machine learning as scalable tools for real-time water quality monitoring, promoting sustainability through informed lake management strategies in India. Full article

Fringe projection profilometry (FPP) has been widely applied in industrial 3D measurement due to its high precision and non-contact advantages. However, FPP often encounters measurement problems with high-dynamic-range objects, consequently impacting phase computation. In this paper, an adaptive exposure time selection method is proposed to calculate the optimal number of exposures and exposure time by using an improved clustering method to divide the region with different reflection degrees. Meanwhile, the phase order sharing strategy is adopted in the phase unwrapping stage, and the same set of complementary Gray code patterns is used to calculate the phase orders under different exposure times. The experimental results demonstrate that the measurement error of the method described in this paper was reduced by 25.4% under almost the same exposure times. Full article

The Kekeya oilfield is located at the southwestern edge of the Tarim Basin, in the southern margin of the Yecheng depression, at the western end of the second structural belt of the northern foothills of the Kunlun Mountains. It is one of the important oil and gas fields in western China, with significant oil and gas resource potential in the X4-X5 section of the Xihepu Formation. This study focuses on the edge of the alluvial fan depositional system, employing various techniques, including core data and well logging data, to precisely characterize the sand body architecture and comprehensively analyze the reservoir architecture in the study area. First, the regional geological background of the area is analyzed, clarifying the sedimentary environment and evolutionary process of the Xihepu Formation. Based on the sedimentary environment and microfacies classification, the sedimentary features of the region are revealed. On this basis, using reservoir architecture element analysis, the interfaces of the reservoir architecture are finely subdivided. The spatial distribution characteristics of the planar architecture are discussed, and the spatial distribution and internal architecture of individual sand body units are analyzed. The study focuses on the spatial combination of microfacies units along the profile and their internal distribution patterns. Additionally, a quantitative analysis of the sizes of various types of sand bodies is conducted, constructing the sedimentary model for the region and revealing the control mechanisms of different sedimentary architectures on reservoir properties and oil and gas accumulation patterns. This study pioneers a quantitative model for alluvial fan fringe in gentle-slope basins, featuring the following: (1) lobe width-thickness ratios (avg. 128), (2) four base-level-sensitive boundary markers, and (3) a retrogradational stacking mechanism. The findings directly inform reservoir development in analogous arid-climate systems. This research not only provides a scientific basis for the exploration and development of the Kekeya oilfield but also serves as an important reference for reservoir architecture studies in similar geological contexts. Full article

Archaeological sites located on the edge of growing cities often struggle to reconcile heritage protection with rapid development. To understand this tension, we examined a 50.83 km² zone around the Western Han Imperial Mausoleums in the Qin-Han New District. Using Landsat images from 1992, 2002, 2012, and 2022, this study applied supervised classification, land-use transfer matrices, and dynamic-degree analysis to trace three decades of land-use change. From 1992 to 2022, built-up land expanded by 29.85 percentage points, largely replacing farmland, which shrank by 35.64 percentage points and became fragmented. Forest cover gained a modest 5.78 percentage points and migrated eastward toward the mausoleums. Overall, urban growth followed a “spread–integrate–connect” pattern along major roads. This study interprets these trends through five interrelated drivers, including policy, planning, economy, population, and heritage protection, and proposes an integrated management model. The model links archaeological pre-assessment with land-use compatibility zoning and active community participation. Together, these measures offer a practical roadmap for balancing conservation and sustainable land management at imperial burial complexes and similar urban fringe heritage sites. Full article