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The flow and heat transfer characteristics of the fluid in the combustor were investigated using numerical simulation in this study. The physical properties of the cooling airflow were fully utilized, and the structure of the combustor was improved. Film hole with novel structure (arc-shaped slot hole) was proposed and compared with cylindrical hole. The optimization schemes for the combustor liner structure were established, in the meanwhile, the influence of different inclinations and slot depths on the temperature distribution of the combustor liner wall was investigated. Compared with the original structure, the average temperature of the target cooling zones in these optimized schemes are reduced by a minimum of 15.12% (227.1 K) and a maximum of 20.65% (351.6 K). A new assessment model (weighted average temperature assessment model) was proposed to provide an effective assessment of the overall cooling effect. The following conclusions were arrived at: high temperature in localized areas is an important reason for the damage of combustor liner wall. Compared to cylindrical hole, the cooling performance of arc-shaped slot hole is better. When the hole type is the same, the larger inclination has higher jet height than the smaller inclination, and the cooling effect is worse. Increasing the slot depth h can improve the cooling efficiency.

As a representative of the fourth-generation light sources, the High Energy Photon Source (HEPS) in Beijing, China, utilizes a multi-bend achromat lattice to obtain an approximately 100 times emittance reduction compared with third-generation light sources. New technologies bring new challenges to operate the storage ring. In order to meet the beam commissioning requirements of HEPS, a new framework for the development of high-level applications (HLAs) has been created. The key part of the new framework is a dual-layer physical module to facilitate the seamless fusion of physical simulation models with the real machine, allowing for fast switching between different simulation models to accommodate the various simulation scenarios. As a framework designed for development of physical applications, all variables are based on physical quantities. This allows physicists to analytically assess measurement parameters and optimize machine parameters in a more intuitive manner. To enhance both extensibility and adaptability, a modular design strategy is utilized, partitioning the entire framework into discrete modules in alignment with the requirements of HLA development. This strategy not only facilitates the independent development of each module but also minimizes inter-module coupling, thereby simplifying the maintenance and expansion of the entire framework. To simplify the development complexity, the design of the new framework is implemented using Python and is called Python-based Accelerator Physics Application Set (Pyapas). Taking advantage of Python's flexibility and robust library support, we are able to develop and iterate quickly, while also allowing for seamless integration with other scientific computing applications. HLAs for both the HEPS linac and booster have been successfully developed. During the beam commissioning process at the linac, Pyapas's ease of use and reliability have significantly reduced the time required for the beam commissioning operators. As a development framework for HLA designed for the new-generation light sources, Pyapas has the versatility to be employed with HEPS, as well as with other comparable light sources, due to its adaptability.

Global warming poses a threat to rice production. Breeding heat-tolerant rice is an effective and economical approach to address this challenge. African rice is a valuable genetic resource for developing heat-tolerant crops due to its intricate mechanism for adapting to high temperatures. Oryza longistaminata, a widely distributed wild rice species in Africa, may harbor an even richer gene pool for heat tolerance, which remains untapped. In this study, we identified three heat tolerance QTLs from O. longistaminata at the seedling stage, including novel heat tolerance loci qTT4 and qTT5. Our findings demonstrated that the O. longistaminata alleles for these two QTLs can enhance the heat tolerance of rice seedlings. Remarkably, qTT5 was mapped to a region spanning approximately 287.2 kb, which contains 46 expressing genes. Through the analysis of Gene Ontology and expression differences under heat induction, we identified four candidate genes. Our results lay the foundation for discovering heat tolerance genes underlying O. longistaminata and developing new genetic resources for heat-tolerant rice breeding.

Automatic detection and recognition of wheel hub text, which can boost the efficiency and accuracy of product information recording, are undermined by the obscurity and orientation variability of text on wheel hubs. To address these issues, this paper constructs a wheel hub text dataset and proposes a wheel hub text detection and recognition model called HubNet. The dataset captured images on real industrial production line scenes, including 446 images, 934 word instances, and 2947 character instances. HubNet is an end-to-end text detection and recognition model, not only comprising conventional detection and recognition heads but also incorporating a feature cross-fusion module, which improves the accuracy of recognizing wheel hub texts by utilizing both global and local features. Experimental results show that on the wheel hub text dataset, the HubNet achieves an accuracy of 86.5%, a recall of 79.4%, and an F1-score of 0.828, and the feature cross-fusion module increases the accuracy by 2% to 4%. The wheel hub dataset and the HubNet offer a significant reference for automatic detection and recognition of wheel hub text.

Abstract Background Minimally invasive vascular intervention (MIVI) is a powerful technique for the treatment of cardiovascular diseases, such as abdominal aortic aneurysm (AAA), thoracic aortic aneurysm (TAA) and aortic dissection (AD). Navigation of traditional MIVI surgery mainly relies only on 2D digital subtraction angiography (DSA) images, which is hard to observe the 3D morphology of blood vessels and position the interventional instruments. The multi-mode information fusion navigation system (MIFNS) proposed in this paper combines preoperative CT images and intraoperative DSA images together to increase the visualization information during operations. Results The main functions of MIFNS were evaluated by real clinical data and a vascular model. The registration accuracy of preoperative CTA images and intraoperative DSA images were less than 1 mm. The positioning accuracy of surgical instruments was quantitatively assessed using a vascular model and was also less than 1 mm. Real clinical data used to assess the navigation results of MIFNS on AAA, TAA and AD. Conclusions A comprehensive and effective navigation system was developed to facilitate the operation of surgeon during MIVI. The registration accuracy and positioning accuracy of the proposed navigation system were both less than 1 mm, which met the accuracy requirements of robot assisted MIVI.

Mucormycosis infected by Actinomucor elegans is relatively serious in the population, so it is urgent need to inactivate Actinomucor elegans. In order to investigate the sterilization effect and mechanisms of contact glow discharge plasma (CGDP) on Actinomucor elegans, the effects of voltage, time and electrolyte on sterilization efficiency were investigated, and the sterilization conditions were confirmed. The sterilization mechanism of CGDP on Actinomucor elegans was explored by analyzing the changes of colony morphology, spore content leakage and peroxidation damage that induced by CGDP treatment. The results showed that CGDP had remarkable sterilization effects on Actinomucor elegans, under the conditions of 560 V, 15 min and Na2SO4 solution, the sterilization rate (η) was up to 90.71%, the colony diameter, spore germination rate and mycelial biomass accumulation all decreased significantly after CGDP treatment, while leakage of intracellular components and degree of peroxidation damage increased, and spore surface became shrinking and rupturing. It was concluded that the Actinomucor elegans was inactivated due to cell membrane integrity destroying induced by CGDP. The results of this paper could provide a reference for the application and mechanism research of CGDP in the field of fungicidal.

Objective To investigate the effectiveness and safety of intravenous remifentanil patient-controlled intravenous analgesia (PCIA) regimen during the active and latency period of the first labor and its influence on plasma prostaglandin E2 (PGE2) in parturients. Methods A total of 60 full-term parturients with a single fetus giving birth vaginally in our center from January 2021 to February 2022 were enrolled in this study. The patients who were willing to receive remifentanil intravenous controlled analgesia formed group R (n=30), and those who refused analgesia formed group C (n=30). Group R received PCA of remifentanil (continuous background infusion of 0.03 μg/kg·min and bolus doses of 0.3 μg/kg with 2 min lockout period in latent phase; continuous background infusion of 0.05 μg/kg·min and bolus doses of 0.4 μg/kg with 2 min lockout period in active phase). Maternal pain score, sedation efficacy, satisfaction, and maternal and fetal adverse reactions were recorded. Neonatal Apgar score and the results of umbilical arterial blood gas analysis were recorded. The levels of PGE2 in R group were determined before and after analgesia. Results Compared to Group C, the mean NRS pain score and the lowest pain score of Group R in latent and active phases were significantly lower (P < 0.05). The overall sedation score and satisfaction score of Group R were obviously higher when compared with Group C (P < 0.05). The incidences of dizziness and drowsiness were statistically higher in the Group R (P < 0.05). No differences were seen in the neonatal Apgar score and the results of umbilical arterial blood gas analysis between the 2 groups (P>0.05). The serum PGE2 levels had no obvious change in Group R before and after analgesia (P>0.05). Conclusion According to the different intensities of labor pain in latent and active phase, appropriate adjustment of remifentanil intravenous controlled analgesia regimen can obviously mitigate maternal labor pain, without obvious maternal and fetal adverse reactions, and has no influence on maternal PGE2 levels.

Accurate oscillating saw tool calibration is an important task for mandibular osteotomy robots to perform precise cutting operations. However, in contrast to traditional tool calibration which just calibrates the tool center position (TCP) or the tool feed axis, both the position and the plane orientation of the saw should be carefully calibrated. Therefore, aiming at this problem, in this paper, we propose a method to carry out oscillating saw calibration by employing an optical stereo vision tracking system. At first, hand–eye calibration is conducted to ascertain the spatial pose of the vision frame within the manipulator’s base frame. Subsequently, employing a probe, the positions of the sawtooth points on the oscillating saw plane are captured within the vision frame. These positions are then translated to the manipulator’s end-effector frame using the positional elimination algorithm proposed in this paper. Finally, the pose of the oscillating saw plane within the manipulator’s end-effector frame is extrapolated from the positions of the three sawtooth points. The result shows that the position errors of the points on the oscillating saw plane are within 0.25 mm and the variance of the plane normal direction is 1.93∘ in the five experiments. This approach enables accurate calibration of the oscillating saw plane’s position and orientation within the manipulator’s end-effector frame. Furthermore, it mitigates the necessity of continual adjustments to the joint angles of the manipulator as required by the “six-point method”. However, this approach is hinged upon the availability of precision-oriented 3D positioning equipment.

This paper analyzes the sources and water quality characteristics of landfill leachate and compares the commonly used treatment technologies of landfill leachate both at home and abroad.In addition,the applications of combined processes with MBR technology at the core in landfill leachate are introduced in detail,including anaerobic membrane bioreactor (AnMBR) technology,anaerobic biological treatment+MBR technology,physicochemical treatment+MBR technology,and the coupling of MBR and NF/RO membrane.Finally,the development trend of MBR technology in landfill leachate treatment is analyzed.

Registration between the intraoperative 2D digital subtraction angiography (DSA) and the pre-operative 3D computed tomography angiography (CTA) is useful in the guidance of vascular interventional surgery (VIS). Because of the flow and diffusion of contrast in vessels, not all the vessels are visible in the DSA, which leads to difficulty in registration. Although the conventional mutual information (MI) and the normalized MI (NMI) perform well in orthopedic surgery, it cannot perform as well in VIS because of the missing vessel in DSA. In this paper, a novel similarity measure, WLMI (Weighted Local Mutual Information), is proposed to perform 2D-3D registration, which uses the patches selected in DSA to find the best match in the DRRs (digital radiography reconstruction) with weighted MI. At first, we choose several ways to measure the richness of block information to select small and scattered patches in the DSA image. Subsequently, different weights are assigned to these patches according to their information abundance by calculating the local MI. With the proposed WLMI, the 2D-3D registration experiments are conducted with the synthetic and real DSA images to CTA vessel model. In synthetic registration, the optimal way to measure information abundance and the optimal weight parameter value are selected. The registration with intact and partially absent vessels are compared with the conventional methods using MAE, mTREproj, and IoU metrics. In the registration of real DSA to CTA model, only IoU is used to compare the difference since the ground-truth cannot be derived. In synthetic registration with vessel excalation test, the mTREproj is 2.9 mm and the IoU is 96.7%. In a real registration test, the IoU reaches 81.3%. Both the synthetic and real DSA registration results show that the proposed WLMI can cope with the problem that partial vessel is invisible in the DSA, and outperformed the conventional methods such as MI and NMI. Therefore, the WLMI is more suitable to be used in the 2D/3D registration task in VIS.

Traditional saliency models designed for natural scene images usually use human visual characteristics to detect the target, but those salient areas in the remote sensing images (RSIs) may not be the targets we are really interested in. Taking both remote sensing image attributes and airport characteristics into account, we put forward a subjective saliency model driven by multi-cues stimulus for the airport's detection (MCS-SSM). Different from traditional saliency models, this model mainly relies on the subjective target detection task to find specific target area eliminating disturbance from other salient targets. Based on the low-level features, we train an LDA classifier by only small target samples and then build an object feature map. In the meantime, the shape information based on line density is extracted to get a shape map. Depending on the fusion result of two saliency maps, we optimize the subjective saliency map with SVM classifier. Moreover, MST density map is generated to suppress background and highlight interesting airport regions in the subjective saliency map. Consequently, MCS-SSM can respectively take the target, the background, and the detection task as multiple cues to quickly locate interest airport targets in RSI with a large cover area. MCS-SSM breaks through the limitations on color, texture, and other low-level characteristics compared with traditional saliency models, which are more targeted to detect the specific targets. The extensive experimental results demonstrate that the proposed MCS-SSM outperforms nine state-of-the-art saliency models. Besides, it has a higher detection rate and better effective performance than other three airport detection approaches.

Vascular image registration is an essential approach to combine the advantages of preoperative 3D computed tomography angiography images and intraoperative 2D X-ray/digital subtraction angiography (DSA) images together. Cardiovascular deformation caused by heartbeat and respiration is one of the most vital factors that affect vascular image registration accuracy. Traditional optimized-based registration methods suffer severely from high computational complexity, which hinders the clinical applications of these methods seriously. To overcome these challenges, we developed a novel multi-channel convolutional neural network (MCNN) that combines a CNN with a periodic vascular diameter variation model. Our method is capable of registering simulated DSA images or real DSA images with their corresponding 3D models in a matter of milliseconds. Our presented MCNN model achieves excellent registration results of three different kinds of cardiovascular patients. The mean absolute error of all six transformation parameters of the MCNN model presented in this paper is less than 1 mm or 1°. The improvement to our MCNN model in registration accuracy is larger than 75% over a single-channel CNN model. Our MCNN method performs more effectively and stable than the state-of-the-art intensity-based methods, especially when vascular deformations occur.

Improving propulsion efficiency holds the promise of enabling the robotic fish to work for a long time with a limited battery in its small body. In this paper, for the swimming of a bionic robotic fish, we present a virtual musculoskeletal control method from the bionic model of the joint driven by agonist muscle and antagonist muscle. A closed-loop method composed of two loops is proposed as a rule of thumb for the speed control of the robotic fish. The outer loop adjusts the swimming speed using the speed deviation; the inner loop regulates the stiffness according to the virtual muscle spindle feedback to fit the water environment. Compared with the proportion control, the evaluation results show that the virtual musculoskeletal methodology increases the efficiency by 3.4% in the steady flow and 7% in the Karman-vortex flow. This algorithm provides a new idea for the joint-space control of the bionic robots that need to reduce the energy consumption of movements.

In order to detect X-corner (or X-point) features more accurately and apace, this article presents a novel and fast detection method based on block-by-block search strategy. Unlike general pixel-by-pixel searching method, the sampling window is first moved along the image block-by-block to find the X-corner candidates rapidly keeping in view the four-step and min-step-distance constraints. During the motion, some overlap is kept between the adjacent sampling windows in order to ensure that all X-corners could have a chance to reside inside, avoiding the possibility of that some X-corners may locate on the edge. Moreover, labeling technology is adopted to prevent duplicate candidates. After the collection of X-corner candidates, the neighborhood variance and centrosymmetry constraints are used to exclude outliers, and the intersection lines is calculated as the sub-pixel position of true X-corner. The experimental results using synthetic and real images show that the presented method approximately takes just about 13 ms to detect 52 X-corners in an image size of 1024 × 768 on a computer having Intel Core i3 CPU at 3.6 GHz and 4GB RAM. The proposed method has faster detection speed compared with the latest methods such as ChESS, SC, and Micron Tracker system while possessing the same or higher detection precision.

Spherical mesoporous NiO powders were synthesized by a hydrothermal-thermal decomposition method, and their morphology and structure were investigated by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and N2 adsorption/desorption analysis. The electrocatalytic performance of NiO powders were systematically studied by cyclic vohammetry (CV), chronoamperometry (CA) and electrochemical impedance spectroscopy (EIS). It is found that the prepared mesoporous NiO powders are in spherical morphology with a specific surface area of 35 m2·g-1 and an average pore size of 15.88 nm. They show good electrocatalytic activity for ethanol oxidation; the oxidation current increases with increasing ethanol concentration and scan rate. The current decay at 0.60 V for 1000 s is as low as 0.075%, indicating good stability. CV, CA and EIS measurements show that ethanol oxidation reaction on the spherical mesoporous NiO is a diffusion-controlled process.

Clogging is a common and difficult problem in subsurface flow wetlands. In this study, 2-4mm, 4-8mm, 8-10mm lightweight ceramsite were used as suspended media beds and 5-10mm gravel was used as traditional substrate bed as control. The effects of these four substrate beds on the purification of water quality and the change of flow capacity in the clogging process in the non-deformable inorganic particle wastewater, deformable inorganic particle wastewater and organic particle wastewater were studied. After the beds were clogged, using the characteristics of lightweight ceramsite floating up and down with water level, the mitigation effect of clogging with water level fluctuation at different heights (10 cm, 20 cm, 30 cm, 40 cm) was explored. The results showed that four kinds of beds had effect on the removal of turbidity and suspended particles. The beds in the treatment of non-deformable inorganic particle wastewater were more likely to cause wetland gap clogging; In the absence of plants, compared with inorganic particles, the clogging degree of substrate in the treatment of organic suspended particulate wastewater was not obvious. After clogging, lightweight ceramsite floats up and down with the water level, three kinds of wetland clogging have been alleviated to some extent.

In this article, a design of honeycomb structure–based soft continuum manipulator is proposed to achieve higher structural strength while keeping compact layout, low material consumption, and thinner wall. At first, a pneumatic deformable cell is designed to simulate the beehive hexagon structure. Secondly, cell units are combined together in a parallel way to form the body module whose stiffness is increased. Thirdly, a gripper module is designed based on the combination of the cell units in one end. Fourthly, several body modules and a gripper module are serially linked to form a soft robot. Fifthly, the basic kinematics of the module is modeled and analyzed. Finally, a prototype made up of silicone rubber is developed for experiments. In the experiments, the soft robot managed to pick up a ball and an egg. The quantitative experiments show that the maximum bending angle was about 90°, and the maximum extending ratio approaches 1.7:1 for a three-module robot test. Reliability test shows a good behavior even though the robot lost its 50% cells. The results show that the new design idea, which is inspired by the cell in biology, is available to improve the reliability of soft robot as expected and enables the robot to move with good flexibility.

In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment.