Positional Relationship Research Articles

Anatomical research of positional relationship between protective channel and sural nerve during Achilles tendon repair using channel assisted minimally invasive repair technique

To evaluate the positional relationship between protective channel and sural nerve while treating acute Achilles tendon rupture with channel assisted minimally invasive repair (CAMIR) technique based on anatomical observations of cadaver specimens. Twelve adult cadaveric lower limb specimens (6 left, 6 right) were utilized. A CAMIR device was implanted at a distance of 4 cm from the proximal end of the specimen to the Achilles tendon insertion. The skin was incised along the tendon's medial side, the sural nerve was dissected, and the positional relationship with the protective channel was observed. The distance from the sural nerve-Achilles tendon intersection to the calcaneal insertion, the vertical distance between protective channel and the calcaneal insertion, and the horizontal distance between the sural nerve and protective channel were measured by using vernier caliper. Anatomical examination demonstrated a variable positional relationship between the sural nerve and protective channel, with the sural nerve positioned above (8 specimens) or below (4 specimens) the protective channel. The distance from the sural nerve-Achilles tendon intersection to the calcaneal insertion was (105.67±14.94) mm, the vertical distance between protective channel and the calcaneal insertion was (93.20±9.57) mm, and the horizontal distance between the sural nerve and protective channel was (0.31±0.14) mm. The use of CAMIR technique for the treatment of acute Achilles tendon rupture can effectively avoid iatrogenic injury to the sural nerve.

Novel Algorithm for Surgical Management of Cervical Ossification of Posterior Longitudinal Ligament: A Retrospective Cohort Study With 2-Year Follow-Up.

With the development of new technologies, the surgical algorithm for ossification of posterior longitudinal ligament (OPLL) in the cervical spine also needs to be updated. The aim of this study is to elucidate a new surgical classification algorithm to guide the choice of surgical approaches for cervical OPLL based on its location and extent. In this algorithm, anterior controllable antedisplacement and fusion (ACAF) will be used as a new surgical option. This is a single-centered, retrospective, cohort study utilizing a novel algorithm based on the following three criteria: (1) the positional relationship between ossification and uncinate process (UP), (2) the K-line, and (3) the ossification segment for surgical decision-making. Patients diagnosed with cervical OPLL who received surgical intervention guided by the algorithm were included. Patient demographics, Japanese Orthopedic Association (JOA) scores, surgical time, imaging data before and 2 years after surgery, and the occurrence of complications were extracted from the database. Paired t-test was used for intragroup comparison, and one-way ANOVA test was used for the intergroup analyses. Based on this novel algorithm, 15 patients with Type I, 8 patients with Type II a, 2 patients with Type II b1, 5 patients with Type II b2 were included. The decision-making for the surgical techniques used in each patient followed the recommendation of the novel algorithm. The postoperative JOA scores of all types of patients improved significantly (p < 0.05), and the invasion rates of vertebral canal had also been significantly reduced (p < 0.05). In terms of restoring cervical curvature, patients with Type I (receiving ACAF) and Type II b2 (receiving laminectomy with instrumented fusion) benefited more from surgery (p < 0.05). A new algorithm guiding the choice of surgical approach for cervical OPLL was validated in a series of 30 patients. Through this analysis, we obtained on their clinical outcomes and complications. ACAF surgery is an ideal choice for Type I patients, with ossification located between UPs, while for patients with ossification exceeding UPs, it is better to perform anterior cervical corpectomy and fusion or posterior surgery.

Autonomous Cargo Grabbing System for Drones Using Cameras and ROS

Abstract. With the rapid development of low-altitude economy, the functional requirements for logistics UAVs are constantly improving. In this paper, an unmanned aerial vehicle system (UAV) is proposed to realize autonomous grasping of goods. First of all, a new type of grasping device is proposed, which can be easily mounted on the UAV. The camera image stream mounted on the UAV was obtained through camera calibration and corrected. Subsequently, the object recognition algorithm was used to process the image frames, successfully identify the goods to be captured, and calculate the position and direction relationship between the UAV and the target cargo. Next, the speed of the drone is adjusted by the PID controller to achieve a stable landing above the target cargo. Then, the drone is equipped with a robotic claw innovatively designed by our team to complete the gripping of the goods. Subsequently, the drone lifted off and began to deliver cargo. Throughout the grabbing process, a laptop equipped with Ubuntu and ROS systems communicates with the drone via Wi-Fi. The feasibility of the whole system was proved by experiments.

Multitask-Based Anti-Collision Trajectory Planning of Redundant Manipulators

During performing multiple tasks of a redundant manipulator, the obstacles affect the sequential order of task areas and the joint trajectories. The end-effector is constrained to visit multiple task areas with an optimal anti-collision path, while the joints are required to move smoothly and avoid predefined obstacles. A special encoding genetic algorithm (SEGA) is proposed for multitask-based anti-collision trajectory planning. Firstly, the spatial occupancy relationship between obstacles and manipulator is developed utilizing the theory of spherical enclosing box and spatial superposition. The obstacles are detected according to the relative position relationship between linear segments and spheres. Secondly, each joint trajectory between adjacent task areas is depicted with a sixth-degree polynomial. Additionally, each joint trajectory is improved via optimizing the unknown six-order coefficient. By searching for optimal sequential order of task areas, optimal collision detection results, and optimal joint trajectories, the multitask-based anti-collision trajectory planning problem is transformed into a parameter optimization problem. In SEGA, the cost function consists of two parts, including the end-effector path length and the variation of joint angles. Moreover, each chromosome consists of three categories of genes, including the sequential order of task areas, the sequential order of joint configurations corresponding to task areas, and the unknown coefficients for anti-collision joint trajectories. Finally, numerical simulations are carried out to verify the proposed method.

Investigation to the vibration characteristics of ultrasonic transducer based on the number of piezoelectric ceramics

As the vibration actuator source, PZT applied on the ultrasonic transducers (UTs) plays a crucial role in the vibration characteristics of UTs. Most conventional research focus on the overall size and positional relationship of PZT stack, while the influence of PZT numbers on vibration characteristics of UTs is seldom reported. In this article, we present a comprehensive investigation between the PZT numbers and vibration characteristics of UTs with identical geometric configurations, specifically UTs with 2 (UT2), 4 (UT4) and 6 (UT6) PZT. The electromechanical equivalent circuit and finite element analysis (FEM) based on PZT numbers are established to investigate the impedance and resonant frequency. Furthermore, the dynamic displacement model of the UTs is proposed to study the influence of PZT numbers on amplitude, and the calculation results are consistent with harmonic response analysis. Finally, the experimental platform is established to test the vibration characteristics of the three types UTs. The results show that the resonant frequency of the transducer is not affected by the numbers of PZT, while the impedance and impedance stability can be improved by the increased PZT numbers. Moreover, the amplitude of UTs is negatively correlated with the numbers of PZT. Through experiments, it is verified that UT2 is suitable for the conditions as the load less than 1000g and amplitude less than 2.2µm, and UT4 is applicable to the other conditions. Although the UT6 exhibits excellent impedance stability, its output power is relatively high and is not suitable for the structure used in this article. The findings suggest that the number of PZTs should be designed based on the operational conditions to improve amplitude output and minimize the loss of power. The presented methods can effectively improve energy consumption and working life, making the UTs greener and more efficient.

Habitat dimensionality and feeding strategies but not temperature as determinants of body size-trophic structure relationship in a marine food web.

Disentangling the determinants of trophic structure is central to ecology. The capacity to capture subjugate and consume a prey (i.e. gape limitation) is a relevant limitation to acquire energy for most organisms, especially those in smaller size ranges. This generates a size hierarchy of trophic positions in which large organisms consume small ones. Body size is tightly correlated to gape limitation and explains a large fraction of variance in the body size-trophic position relationship. However, a considerable fraction of variance still remains to be explained. Consumer search space dimensionality (2D or 3D) and feeding strategies, temperature and the size structure of primary producers can alter the trophic structure, but tests based on information from natural food webs are scarce. We generated specific predictions about the body size trophic position relationship and evaluated them using information from a subtropical South Atlantic coastal marine ecosystem: benthic realm (2D, rocky shore and sandy beach) and the pelagic realm (3D). We characterized this marine coastal food web based on stable isotopes of carbon and nitrogen from 256 samples from primary producers (macroalgae and phytoplankton) to large predators (sand shark) in summer and winter. Consumer body size encompassed six orders of magnitude in weight from 10-2 to 6 × 104 g. Isotopic signal corresponded to an integration of carbon sources from basal consumers to top predators. The body size-trophic position relationship showed a linear positive association with different slopes for the benthic and pelagic environments. This implies a smaller predator prey size ratio for pelagic (3D) with respect to benthic consumers (2D) as theoretically expected. No seasonal differences were found in slopes and most of the overall variance in benthic environments was largely explained by feeding strategies of the different taxonomic groups. We provide an integrated evaluation on the role of body size, consumer search space and feeding strategy to understand the determinants of trophic position. Results demonstrate that integrating gape limitation hypothesis, the dimensionality of consumer search space and feeding strategies into a formal robust framework to understand trophic structure is feasible even in complex natural ecosystems.

A Study on Lymph Node Distribution in the Main Lymph Node Area for Left-sided Colon Cancer.

In advanced left-sided colorectal cancer, cutting the root of the inferior mesenteric artery (IMA) branching from the aorta is recommended for complete lymph node dissection. However, this procedure sometimes causes severe complications. This study aimed to elucidate the lymph nodes' distribution around the IMA and identify the most critical sites for lymph node dissection. This study included 30 consecutive patients with left-sided colorectal cancer who underwent curative resection with main lymph node dissection in a single institution between January and June of 2022. The mesenteric sections (main lymph nodes, IMA, left colic artery [LCA], and inferior mesenteric vein) were removed from the surgically excised specimen. Subsequently, whole-tissue sections were prepared and stained with hematoxylin and eosin. The positional relationships between each blood vessel and respective lymph nodes were then assessed using the pathological findings. The main lymph nodes were identified in 26 out of 30 patients. The total number of dissected lymph nodes per patient was 0-30 (average: 5.3), and the median distance from the IMA to the main lymph node was 7.61 mm (1.87-43.26 mm). Dividing the lymph nodes into segments, we found 18%, 46%, and 36% of the lymph nodes in the proximal, middle, and distal segments, respectively. Additionally, all lymph nodes were found outside of the IMA sheath surrounding each arterial wall. In left-sided colorectal cancer, the main lymph nodes are mostly located around the LCA bifurcation, which may be essential to ensure main lymph node dissection for advanced stage cases.

Dogs with severe tracheal flattening exhibit lower degrees of left lateralization of the cervical esophagus.

Herein, we investigated the positional relationship between the cervical esophagus and trachea using computed tomography (CT) images in dogs with tracheal flattening. From these CT images, the ratio of the tracheal diameters in the short (vertical) and long (horizontal) axes of the tracheal ring (S/L ratio) and the vertebra - trachea - esophagus (VTE) angle were measured at the point from the 3rd cervical (C3) to the 3rd thoracic vertebra (T3) levels. The VTE angle in dogs with tracheal flattening with an S/L ratio under 0.24 tended to be smaller than the angles at the level from C4 to T2 in dogs with an S/L ratio over 0.25. The positional relationship between the esophagus and trachea seems to be possibly related to tracheal cross-sectional shape.

DPNet: Scene text detection based on dual perspective CNN-transformer.

With the continuous advancement of deep learning, research in scene text detection has evolved significantly. However, complex backgrounds and various text forms complicate the task of detecting text from images. CNN is a deep learning algorithm that automatically extracts features through convolution operation. In the task of scene text detection, it can capture local text features in images, but it lacks global attributes. In recent years, inspired by the application of transformers in the field of computer vision, it can capture the global information of images and describe them intuitively. Therefore, this paper proposes scene text detection based on dual perspective CNN-transformer. The channel enhanced self-attention module (CESAM) and spatial enhanced self-attention module (SESAM) proposed in this paper are integrated into the traditional ResNet backbone network. This integration effectively facilitates the learning of global contextual information and positional relationships of text, thereby alleviating the challenge of detecting small target text. Furthermore, this paper introduces a feature decoder designed to refine the effective text information within the feature map and enhance the perception of detailed information. Experiments show that the method proposed in this paper significantly improves the robustness of the model for different types of text detection. Compared to the baseline, it achieves performance improvements of 2.51% (83.81 vs. 81.3) on the Total-Text dataset, 1.87% (86.07 vs. 84.2) on the ICDAR 2015 dataset, and 3.63% (86.72 vs. 83.09) on the MSRA-TD500 dataset, while also demonstrating better visual effects.

Atomic force microscopy wide-field scanning imaging using homography matrix optimization

During the offline combination of multiple atomic force microscopy (AFM) images, changes in probe displacement can be affected by dynamic noise, leading to dislocation and tearing in the stitching. To overcome this, we designed a homography matrix optimization method to describe the relative positional relationship between images by constructing the original image matrix and applying singular value decomposition to denoise the homography matrix. Additionally, we implemented a scale-invariant feature transform (SIFT) to extract feature points. To verify the effectiveness of this method, the SIFT + RANSAC (R), SIFT + affine transformation (AT), and oriented FAST and rotated BRIEF (ORB) algorithms were compared with the proposed algorithm. The experimental results demonstrate that the proposed method precisely computes the transformation matrix, thereby guaranteeing the geometric consistency of mosaic imaging. The proposed method preserves the intricate details of the original image and enhances the stitching quality of wide-field images.

Signal-receiving UAV Positioning Model Based on Geometric Analysis

A drone is an aerial vehicle without a pilot or controller that is remotely controlled using aerodynamics to fulfil a designated task under certain circumstances. With the encouragement and support of national policies, the development of China's UAV industry has a good prospect. In real life, location information is the key information for UAVs to accurately complete operations and realise mission requirements, and the importance of its accurate positioning is self-evident. For the UAV localisation model, the bias-free localisation model is established first, and then the localisation model in the case of bias is solved on this basis. When there is a deviation in the received signal UAV, the UAV may be located outside the circle, on the circle, and inside the circle. Specifically divided into four scenarios, see Figure 1-4. (Analysed: outside the circle: θ1’&lt;θ1; inside the circle: θ1’&gt;θ1; circle on the left: θ2&gt;θ2’, right: θ2&lt;θ2’; no deviation: θ1’=θ1, θ2’&lt;θ2). When the position of the passive receiving signal UAV does not exist deviation, according to the position relationship obtained four cases, respectively, the establishment of the quadrilateral, the use of sinusoidal theorem to obtain the receiving signal UAV positioning model, the same can be obtained under the existence of deviation, the specific positioning model of the receiving signal UAV.

Multi-line laser 3D reconstruction method based on spatial quadric surface and geometric estimation

The traditional multi-line laser 3D reconstruction is based on binocular epipolar constraints and the equation of the laser optical plane. Firstly, matching points are identified based on the epipolar constraints. Then, the correct matching points are selected based on the optical plane equation of the multi-line laser. Finally, 3D reconstruction is performed using the selected matching points. In actual production processes involving multi-line lasers, noticeable distortion occurs due to the projection of Diffractive Optical Elements (DOE) at a large angle. This results in curved laser light planes and curved reflections on the measured objects. Under such circumstances, efficiently screening matching points using the traditional method based on the laser plane equation becomes challenging. Additionally, inherent noise in multi-line laser systems introduces errors in extracted laser center coordinates, making it impossible to directly obtain high-precision 3D data. To address these issues, this paper proposes a method that utilizes spatial quadric surfaces and geometric estimation for completing multi-line laser 3D reconstructions. By analyzing the distortion principle of DOE and the positional relationship after optical diffraction, the multi-line laser manifests as a quadric surface on the optical output plane. Consequently, by calibrating the equations of the quadric surface and applying binocular polar constraints, suitable matching points for the multi-line laser can be chosen. Once an accurate matching point is identified, a minimum geometric distance estimation can be established based on the distance constraint between the point and its corresponding epipolar line. This distance represents the separation between the left and right camera’s laser center points and their respective epipolar lines. Utilizing this estimate of the minimum geometric distance, a refined calculation can be performed to better satisfy epipolar constraints and obtain new matching points. Ultimately, utilizing these new matching points enables the completion of 3D reconstruction for multi-line lasers. In comparison with methods relying on spatial plane and epipolar constraints, our algorithm exhibits a superior degree of matchability and accuracy.According to multiple groups of test data, the average error before optimization is 0.3126 mm, and can be increased to 0.0336 mm after optimization.

The influence of equilibrium points and initial values on multistability of a multi-scroll chaotic system and predefined-time synchronization

Abstract In order to explore the effect of the initial value on the symmetry of the coexisting attractor, a novel multi-scroll chaotic system is designed in this paper. The system is proved to be chaotic by analysing the phase diagram, Lyapunov exponential spectrum and dissipativity of the system. Then the equilibrium point of the system is investigated and it is found that the system has four symmetric saddle focus of index 2. By analysing the dynamical behaviour of the system, it is found that the system has a special kind of multistability. Combining the properties of the orbits near the saddle focus of indicator 2, the reason for this special multistability is explained, and the effect of the positional relationship between the initial value and the saddle focus on the symmetry of the coexisting attractors is illustrated, which provides a new way of thinking to analyse the symmetric coexistence of chaotic systems. In order to verify the feasibility and application value of the system, simulation circuits are designed and predefined-time synchronization between systems of different dimensions is achieved.

Improved YOLOv8n for Lightweight Ship Detection

Automatic ship detection is a crucial task within the domain of maritime transportation management. With the progressive success of convolutional neural networks (CNNs), a number of advanced CNN models have been presented in order to detect ships. Although these detection models have achieved marked performance, several undesired results may occur under complex maritime conditions, such as missed detections, false positives, and low detection accuracy. Moreover, the existing detection models endure large number of parameters and heavy computation cost. To deal with these problems, we suggest a lightweight ship model of detection called DSSM–LightNet based upon the improved YOLOv8n. First, we introduce a lightweight Dual Convolutional (DualConv) into the model to lower both the number of parameters and the computational complexity. The principle is that DualConv combines two types of convolution kernels, 3x3 and 1x1, and utilizes group convolution techniques to effectively reduce computational costs while processing the same input feature map channels. Second, we propose a Slim-neck structure in the neck network, which introduces GSConv and VoVGSCSP modules to construct an efficient feature-fusion layer. This fusion strategy helps the model better capture the features of targets of different sizes. Meanwhile, a spatially enhanced attention module (SEAM) is leveraged to integrate with a Feature Pyramid Network (FPN) and the Slim-neck to achieve simple yet effective feature extraction, minimizing information loss during feature fusion. CIoU may not accurately reflect the relative positional relationship between bounding boxes in some complex scenarios. In contrast, MPDIoU can provide more accurate positional information in bounding-box regression by directly minimizing point distance and considering comprehensive loss. Therefore, we utilize the minimum point distance IoU (MPDIoU) rather than the Complete Intersection over Union (CIoU) Loss to further enhance the detection precision of the suggested model. Comprehensive tests carried out on the publicly accessible SeaShips dataset have demonstrated that our model greatly exceeds other algorithms in relation to their detection accuracy and efficiency, while reserving its lightweight nature.

A Three-Dimensional Modeling Approach for Carbon Nanotubes Filled Polymers Utilizing the Modified Nearest Neighbor Algorithm.

Carbon nanotubes (CNTs) are extensively utilized in the fabrication of high-performance composites due to their exceptional mechanical, electrical, and thermal characteristics. To investigate the mechanical properties of CNTs filled polymers accurately and effectively, a 3D modeling approach that incorporates the microstructural attributes of CNTs was introduced. Initially, a representative volume element model was constructed utilizing the modified nearest neighbor algorithm. During the modeling phase, a corresponding interference judgment method was suggested, taking into account the potential positional relationships among the CNTs. Subsequently, stress-strain curves of the model under various loading conditions were derived through finite element analysis employing the volume averaging technique. To validate the efficacy of the modeling approach, the stress within a CNT/epoxy resin composite with varying volume fractions under different axial strains was computed. The resulting stress-strain curves were in good agreement with experimental data from the existing literature. Hence, the modeling method proposed in this study provides a more precise representation of the random distribution of CNTs in the matrix. Furthermore, it is applicable to a broader range of aspect ratios, thereby enabling the CNT simulation model to more closely align with real-world models.

Organizational ethics and position relationship moderators among knowledge workers: a regional study of Poland

ABSTRACT This research explores organizational ethics among knowledge workers using ICT4Ds in regional enterprises in Poland before, during, and after the COVID-19 pandemic. The study addresses the importance of understanding how ethics in organizations, particularly ethical optimism, corporate social responsibility, and top management action, have evolved across these periods. This topic is crucial as organizational ethics influence employee behavior and decision-making, particularly during crises. The research question focuses on how organizational ethics, influenced by gender and the pandemic, differ by position. Online surveys and random sampling were employed to collect data among knowledge workers (139 before, 134 during, and 98 after the pandemic). The study applied multivariate statistical methods, including variance analysis and causal moderation. Findings were that superiors rated organizational ethics higher than subordinates, and ethical optimism fluctuated, rising during the pandemic and dropping afterward. The study contributes to understanding the role of gender and crises as moderators in organizational ethics, benefiting managers and policymakers.

Optimized position analysis of multi-directional active mounting system based on quantification formula

This paper mainly studies the influence of active mounting system for vehicle engine vibration from both theoretical and experimental aspects. First, an active mounting system that considers both horizontal and vertical directions is proposed, modeled, analyzed and verified. The structure contains a bent beam representing the engine, two sets of actuator and elastomer forming active paths, and a straight beam representing the chassis. Second, the force and phase of the active mounts at each location combination are calculated based on static and dynamic methods. The dynamic analysis method is used to examine how the control signal changes with the input signal to learn the correlation between them. The static analysis is employed to obtain the change in force applied to the paths when the position of the input signal changes and to find the optimized placement criteria. Through the position relationship between force and mounting, a specific position where the applied force is relatively small was considered the optimized position of the active mounting system. Finally, these criteria were verified with experiments and the results are matched well with each other.

LGTDA: Bandwidth exhaustion attack on Ethereum via dust transactions

Dust attacks typically involve sending a large number of low-value transactions to numerous addresses, aiming to facilitate transaction tracking and undermine privacy, while simultaneously disrupting the market and increasing transaction delays. These transactions not only impact the network but also incur significant costs. This paper introduces a low-cost attack method called LGTDA, which achieves network partitioning through dust attacks. This method hinders block synchronization by consuming node bandwidth, leading to denial of service(DoS) for nodes and eventually causing large-scale network partitioning. In LGTDA, the attacker does not need to have real control over the nodes in the network, nor is there a requirement for the number of peer connections to the nodes; the attack can even be initiated by simply invoking RPC services to send transactions. Under the condition of ensuring the validity of the attack transactions, the LGTDA attack sends a large volume of low-value, high-frequency dust transactions to the network, relying on nodes for global broadcasting. This sustained attack can significantly impede the growth of block heights among nodes, resulting in network partitioning. We discuss the implications of the LGTDA attack, including its destructive capability, low cost, and ease of execution. Additionally, we analyze the limitations of this attack. Compared to grid lighting attacks, the LGTDA attack has a broader impact range and is not limited by the positional relationship with the victim node. Through experimental validation in a controlled environment, we confirm the effectiveness of this attack.

A star selection strategy based on MDS and fast convex hull algorithm in COSPAS-SARSAT system

Abstract The space segment of the current COSPAS-SARSAT system is mainly supported by the Galileo system, and the positioning technology used is generally three-star time-difference positioning. Most of the antennas equipped in the Mission Control Centre (MCC) are not omnidirectional. In the case of Source of Search and Rescue (SAR) in a heavily shaded environment, it is necessary to use the different orbit time-sharing single satellite geolocations using TDOA, and the time-sharing will generate more satellite position data. In order to achieve the higher positioning accuracy of the solution, it is necessary to select the appropriate time and optimal geometrical distribution from the satellite positions. In this paper, we propose a satellite selection strategy based on Multiple Dimensional scaling (MDS) data degradation and a fast convex hull algorithm. The three-dimensional satellite data are downscaled to two-dimensional while maintaining their relative positional relationships, and the two-dimensional convex hull algorithm is used for Geometric Dilution of Precision (GDOP) minimum search star selection. By simulating the satellite position data in different orbits and time-sharing to complete the localization solution, the results show that compared with the traditional satellite selection method, the satellite selection strategy proposed in this paper is able to achieve better localization accuracy in a shorter period of time.

In-situ study on the differential evolution of He bubbles in the multilayer oxide of Fe9Cr1.5W0.4Si F/M steel corroded in lead-bismuth eutectic

The combined effects of corrosion and irradiation on nuclear components have been an important but not yet fully revealed topic. Here, the irradiation behavior of the oxide scale formed on F/M steel after lead-bismuth corrosion was in-situ investigated during He+ irradiation. The results showed that the oxide scale included a Fe3O4 outer oxide layer, a nanograin Fe(FexCr2-x)O4 spinel inner oxide layer, and an internal oxide layer. He bubbles formed in Fe3O4, Fe-Cr spinel and F/M steel were polygon, irregular elongated pores and small spheres, respectively. These differences were attributed to variations in defect generation, migration, and corrosion-induced crystal defects in different oxides. Numerous corrosion-induced nanograin boundaries and vacancies in Fe-Cr spinel exhibited more effective absorption of irradiation-induced defects. Moreover, rhombic perfect dislocation loops were detected in Fe3O4 at the late stage of irradiation, their relative positional relationship with He bubbles indicated a potential interaction between bubbles and loops.