Current Issue : January-March Volume : 2026 Issue Number : 1 Articles : 6 Articles
To address the issue of insufficient contrast in conventional X-ray absorption imaging for biological soft tissues and weakly absorbing materials, this paper proposes a beam tracking X-ray phase-contrast imaging system using a conventional X-ray source. A periodic pinhole array mask is placed between the X-ray source and the sample to spatially modulate the X-ray beam, dividing it into multiple independent sub-beams. Each sub-beam is deflected due to the modulation effect of the sample, resulting in slight positional shifts in the intensity patterns formed on the detector. The experiments employ an X-ray source with a 400 μm focal spot and use a two-dimensional step-scanning approach to acquire image sequences of various samples. The experimental results show that this method can extract the edge profile and structural changes in the samples to some extent, and it demonstrates good contrast and detail recovery under weak absorption conditions. These results suggest that this method has certain application potential in material inspection, non-destructive testing, and related fields....
Virtual networks have emerged as a promising solution for enabling diverse users to efficiently share bandwidth resources over optical network infrastructures. Despite the invention of various schemes aimed at ensuring secure isolation among virtual networks, the security of data transfer in virtual networks remains a challenging problem. To address this challenge, the concept of evolving traditional optical networks into key programmable optical networks (KPONs) has been proposed. Inspired by this, this paper delves into the establishment of secure virtual networks over KPONs, in which the informationtheoretically secure keys can be supplied for ensuring the information-theoretic security of data transfer within virtual networks. A layered architecture for secure virtual network provisioning over KPONs is proposed, which leverages software-defined networking to realize the programmable control of optical-layer resources. With this architecture, a heuristic algorithm, i.e., the key adaptation-based secure virtual network provisioning (KA-SVNP) algorithm, is designed to dynamically allocate key resources based on the adaption between the key supply and key demand. To evaluate the proposed solutions, an emulation testbed is established, achieving millisecond latencies for secure virtual network establishment and deletion. Moreover, numerical simulations indicate that the designed KA-SVNP algorithm performs superior to the benchmark algorithm in terms of the success probability of secure virtual network requests....
This work aimed to quantify axial deformations of a human premolar during occlusion with its antagonist and to compare them with the same premolar restored with a ceramic crown. The deformations were put under stress using a mechanical press with a force ranging from 1 to 100 Newtons. These deformations were quantified using the optical interferometry technique with a laser source (633 nm, 0.95 mW). Using a CMOS camera, interference fringes were obtained, stored, and subsequently processed. The premolars were restored with Cerasmart GC ceramic, using the CAD-CAM system. The average deformations of healthy premolars were found to be in a range of 0.69 to 1.74 μm, while the restored ones were deformed in a range of 0.53 to 1.10 μm. The results of this work showed that the Cerasmart ceramic material had similar properties to those of the natural tooth for small forces. However, for higher forces, the ceramics increased the coronal stiffness of the tooth. This modified the optimal combination of stiffness, strength, and resilience between the enamel and dentin, causing a decrease in the tooth’s ability to dissipate energy; therefore, the tooth could receive more stress. The observed mechanical properties lead to the conclusion that the Cerasmart material can be indicated for the restoration of anterior and premolar teeth in most cases where a fixed prosthesis is required....
With the increasing adoption of wide-bandgap semiconductors such as SiC and GaN in high-power electronics, the thermal management of semiconductor devices has become critical. High thermal conductivity thermal interface materials (TIMs) are essential to minimize thermal contact resistance. Advanced fillers such as graphene, diamond nanosheets, and hexagonal boron nitride (h-BN) have been proposed, and their effectiveness strongly depends on the spatial continuity and orientation of the filler network. Excessive filler loading degrades mechanical strength and flexibility. Visualizing the spatial distribution of thermal conductivity is thus essential to optimize the filler structure. This study examines the correlation between the spatial distribution of thermal diffusivity and the internal filler structure in composite materials, employing both experimental and numerical methods. We proposed and have been developing a lock-in thermography-based laser periodic heating method to obtain the spatial thermal diffusivity distribution of composites [1]. In this study, the internal fiber-resin structure of CFRP (carbon fiber reinforced plastic) specimens was visualized using synchrotron X-ray computed tomography (SR-CT), meshed using GeoDict, and used to perform transient heat conduction simulations in ANSYS Fluent. The thermal diffusivity distribution obtained from simulations was compared with that measured by the lock-in thermography method....
Purpose: Timely removal of ureteral stents is critical to prevent complications such as infection, discomfort and stent encrustation or fragmentation, as well as stone formation associated with neglected stents. Current decisions, however, rely heavily on subjective interpretation of postoperative imaging. This study introduces a semi-automated imageprocessing algorithm that quantitatively evaluates stent morphology, aiming to support objective and reproducible decision-making in minimally invasive urological care. Methods: Two computational approaches were developed to analyze morphological changes in ureteral stents following surgery. The first method employed a vector-based analysis, using the FitLine function to derive unit vectors for each stent segment and calculating inter-vector angles. The second method applied a slope-based analysis, computing gradients between coordinate points to evaluate global straightening of the ureter over time. Results: The vector-angle method did not demonstrate significant temporal changes (p = 0.844). In contrast, the slope-based method identified significant ureteral straightening (p < 0.05), consistent with clinical observations. These results confirm that slope-based quantitative analysis provides reliable insight into postoperative morphological changes. Conclusions: This study presents an algorithm-based and reproducible imaging analysis method that enhances objectivity in postoperative assessment of ureteral stents. By aligning quantitative image processing with clinical decision support, the approach contributes to precision medicine and addresses the absence of standardized criteria for stent removal....
Identifying concealed explosives in X-ray backscatter (XRBS) imagery remains a critical challenge, primarily due to low image contrasts, cluttered backgrounds, small object sizes, and limited structural details. To address these limitations, we propose YOLOv11-XRBS, an enhanced detection framework tailored to the characteristics of XRBS images. A dedicated dataset (SBCXray) comprising over 10,000 annotated images of simulated explosive scenarios under varied concealment conditions was constructed to support training and evaluation. The proposed framework introduces three targeted improvements: (1) adaptive architectural refinement to enhance multi-scale feature representation and suppress background interference, (2) a Size-Aware Focal Loss (SaFL) strategy to improve the detection of small and weak-feature objects, and (3) a recomposed loss function with scale-adaptive weighting to achieve more accurate bounding box localization. The experiments demonstrated that YOLOv11-XRBS achieves better performance compared to both existing YOLO variants and classical detection models such as Faster R-CNN, SSD512, RetinaNet, DETR, and VGGNet, achieving a mean average precision (mAP) of 94.8%. These results confirm the robustness and practicality of the proposed framework, highlighting its potential deployment in XRBS-based security inspection systems....
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