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In the process of launching guided projectile under the conventional system, it is difficult to effectively obtain the precise navigation parameters of the projectile in the high dynamic environment. Aiming at this problem, this paper describes a new system of guided ammunition based on tail spin reduction. After analyzing the mechanism of the ammunition's tail spin reduction, a navigation method of large scale difference tail control simple guided ammunition based on speed constraint is proposed. In this method, the corresponding navigation constraints can be carried out by combining the rotation speed state of the ammunition itself, and the optimal solution of navigation parameters during the flight of the missile can be obtained by Extended Kalman Filter (EKF). Finally, the performance of the proposed method was verified by the simulation environment, and the hardware-in-the-loop simulation test and flight test were carried out to verify the performance of the method in the real environment. The experimental results show that the proposed method can achieve the optimal estimation of navigation parameters for simple guided ammunition with large-scale difference tail control. Under the conditions of simulation test and hardware-in-loop simulation test, the position and velocity errors calculated by the method in this paper converged. Under the condition of flight test, the spatial average error calculated by the method described in this paper is 6.17 m, and the spatial error of the final landing point is 3.50 m. Through this method, the accurate acquisition of navigation parameters in the process of projectile launching is effectively realized.

In response to the localization challenges posed by multi-modal motion mode transitions during the locomotion of tracked-wheel robots in sheltered spaces, this paper presents a combination localization method based on Inertial Navigation System/Odometry (INS/OD). Leveraging the unique locomotion structure of tracked-wheel robots, a multi-modal odometry motion model and non-holonomic constrained (NHC) velocity model are established. A closed-loop extended Kalman filter is employed to construct the combination localization model, facilitating real-time computation and correction of the robot’s heading angle using the odometry motion model, effectively mitigating system errors and preventing heading divergence. The wheeled-track robot was subjected to outdoor and underground tunnel real-world localization tests. The results demonstrate that the proposed combined localization method achieved an absolute positioning accuracy of the wheeled-track robot within 0.3578 meters in outdoor experiments. This accounts for only 0.31% of the total distance traveled in the outdoor experiments, with an average error of 0.1611 meters. In the context of relative positioning within the underground tunnel, the localization error was measured at 0.2143 meters, representing a mere 0.2306% of the total distance covered in the tunnel. These findings affirm the capability of the combined localization method to meet the practical localization requirements of the wheeled-track robot, both in outdoor and in-sheltered space tunnel scenarios.

As the core component of the all-metal micro resonant gyroscope, the structural parameters and form and position errors of the resonator significantly influence its vibration characteristics, and consequently, the accuracy of the gyroscope. By establishing the finite element model of an ideal hemispherical resonator and optimizing the meshing method, we refined the frequency difference to 0.1 Hz, enhancing the accuracy of the simulation model. Through finite element simulation, we examined the impact of various structural parameters and processing errors on the natural frequencies of each mode. We analyzed how form and position errors, including shell thickness error, central axis error, equatorial plane error, and edge rectangular tooth position error, affect the frequency splitting of the resonator. We provided optimization suggestions for the structural parameters, ensuring frequency splitting variations of less than 1 Hz. Theoretical modeling and simulation analysis indicated that the primary factors influencing the vibration modes and frequency splitting are the rectangular tooth structure and shell thickness. Following the optimized parameters, the frequency splitting of the All-Metal Micro Resonant Hemisphere was reduced by an order of magnitude to 14 Hz, demonstrating that these optimized conditions can significantly enhance the resonator’s performance.

Metal-μhemispherical resonant gyros (M-μHRGs) are widely used in highly dynamic navigation systems in extreme environments due to their high accuracy and structural stability. However, the effect of temperature variations on the capacitance characteristics of M-μHRGs has not been fully investigated, which is crucial for optimizing the performance of the gyro. This study aims to systematically analyze the effect of temperature on the static and dynamic capacitances of M-μHRGs. In this study, an M-μHRG structure based on a 16-tooth metal oscillator is designed, and conducted simulation experiments using non-contact capacitance measurement method and COMSOL Multiphysics 6.2 finite element simulation software in the temperature range of 233.15 K to 343.15 K. The modeling analysis of the static capacitance takes into account the thermal expansion effect, and the results show that static capacitance remains stable across the measured temperature range, with minimal effect from temperature. The dynamic capacitance exhibits significant nonlinear variations under different temperature conditions, especially in the two end temperature intervals (below 273.15 K and above 313.15 K), where the capacitance values show local extremes and fluctuations. In order to capture this nonlinear behavior, the experimental data were smoothed and fitted using the LOESS method, revealing a complex trend of the capacitance variation with temperature. The results show that the M-μHRG has good capacitance stability in the mid-temperature range, but its dynamic performance is significantly affected at extreme temperatures. This study provides a theoretical reference for the optimal design of M-μHRGs in high- and low-temperature environments.

For the problem of difficult tracking of small leaks in buried gas pipelines, a video detection of small leaks in buried gas pipelines method is proposed for the detection robot inside buried gas pipelines. Firstly, collecting images and videos of leaks inside buried gas pipelines to establish a dataset. Secondly, build a video detection model for small leaks in buried gas pipelines, introduce a bidirectional feature pyramid network into YOLOv5s (You Only Look Once), and build a feature fusion network to enhance the model’s ability to fuse small leaks. Thirdly, building a small target detection layer and a small target detection head in the YOLOv5s classification prediction network enhances the model’s ability to fuse small leaks. Fourthly, the video detection model for small leaks in buried gas pipelines is trained using the dataset. Lastly, the model’s video detection effect of small leaks is verified through leak detection experiments in various situations. The experimental results show that the precision rate of this method is 94.1%, the recall is 94.8%, and the average precision is 94.5%, which has a good detection effect and strong generalization ability.

Abstract Background Coinfection with HIV and Plasmodium parasites is fairly common, but the sequence of infection with these two pathogens and their impact on disease progression are poorly understood. Methods A Chinese rhesus macaque HIV and Plasmodium coinfection model was established to compare the impact of pre-existing and subsequent malaria on the progression of SIV infection. Results We found that a pre-existing malaria caused animals to produce a greater number of CD4+CCR5+ T cells for SIV replication, resulting in higher viral loads. Conversely, subsequent malaria induced a substantially larger proportion of CD4+CD28highCD95high central memory T cells and a stronger SIV-specific T cell response, maintained the repertoire diversity of SIV-specific T cell receptors, and generated new SIV-specific T cell clonotypes to trace SIV antigenic variation, resulting in improved survival of SIV-infected animals. Conclusion The complex outcomes of this study may have important implications for research on human HIV and malaria coinfection. The infection order of the two pathogens (HIV and malaria parasites) should be emphasized. Video abstract

ObjectiveFondaparinux is a synthetic anticoagulant for the prevention of venous thromboembolism (VTE), and its administration in Chinese cancer patients is rarely reported. This study aimed to assess the efficacy and safety of fondaparinux in preventing VTE in Chinese cancer patients.MethodsA total of 224 cancer patients who received fondaparinux treatment were reviewed in this single-arm, multicenter, retrospective study. Meanwhile, VTE, bleeding, death, and adverse events of those patients in the hospital and at 1 month after treatment (M1) were retrieved, respectively.ResultsThe in-hospital VTE rate was 0.45% and there was no (0.00%) VTE occurrence at M1. The in-hospital bleeding rate was 2.68%, among which the major bleeding rate was 2.23% and the minor bleeding rate was 0.45%. Moreover, the bleeding rate at M1 was 0.90%, among which both the major and minor bleeding rates were 0.45%. The in-hospital death rate was 0.45% and the death rate at M1 was 0.90%. Furthermore, the total rate of adverse events was 14.73%, including nausea and vomiting (3.13%), gastrointestinal reactions (2.23%), and reduced white blood cells (1.34%).ConclusionFondaparinux could effectively prevent VTE with low bleeding risk and acceptable tolerance in cancer patients.

The roll angular rate is much crucial for the guidance and control of the projectile. Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate. Nevertheless, the radial magnetometer signal is modulated by the high-speed rotation, thus the roll angular rate can be achieved by extracting the instantaneous frequency of the radial magnetometer signal. The objective of this study is to find out a precise instantaneous frequency extraction method to obtain an accurate roll angular rate. To reach this goal, a modified spline-kernelled chirplet transform (MSCT) algorithm is proposed in this paper. Due to the nonlinear frequency modulation characteristics of the radial magnetometer signal, the existing time-frequency analysis methods in literature cannot obtain an excellent energy concentration in the time-frequency plane, thereby leading to a terrible instantaneous frequency extraction accuracy. However, the MSCT can overcome the problem of bad energy concentration by replacing the short-time Fourier transform operator with the Chirp Z-transform operator based on the original spline-kernelled chirplet transform. The introduction of Chirp Z-transform can improve the construction accuracy of the transform kernel. Since the construction accuracy of the transform kernel determines the concentration of time-frequency distribution, the MSCT can obtain a more precise instantaneous frequency. The performance of the MSCT was evaluated by a series of numerical simulations, high-speed turntable experiments, and real flight tests. The evaluation results show that the MSCT has an excellent ability to process the nonlinear frequency modulation signal, and can accurately extract the roll angular rate for the high spinning projectiles.

Rural environments and microbiota are linked to a reduction in the prevalence of allergies. However, the mechanism underlying the reduced allergies modulated by rural residency is unclear. Here, we assessed gut bacterial composition and metagenomics in urban and rural children in the EuroPrevall-INCO cohort. Airborne dusts, including mattress and rural henhouse dusts, were profiled for bacterial and fungal composition by amplicon sequencing. Mice were repeatedly exposed to intranasal dust extracts and evaluated for their effects on ovalbumin (OVA)-induced allergic airway inflammation, and gut microbiota restoration was validated by fecal microbiota transplant (FMT) from dust-exposed donor mice. We found that rural children had fewer allergies and unique gut microbiota with fewer Bacteroides and more Prevotella. Indoor dusts in rural environments harbored higher endotoxin level and diversity of bacteria and fungi, whereas indoor urban dusts were enriched with Aspergillus and contained elevated pathogenic bacteria. Intranasal administration of rural dusts before OVA sensitization reduced respiratory eosinophils and blood IgE level in mice and also led to a recovery of gut bacterial diversity and Ruminiclostridium in the mouse model. FMT restored the protective effect by reducing OVA-induced lung eosinophils in recipient mice. Together, these results support a cause-effect relationship between exposure to dust microbiota and allergy susceptibility in children and mice. Specifically, rural environmental exposure modulated the gut microbiota, which was essential in reducing allergy in children from Southern China. Our findings support the notion that the modulation of gut microbiota by exposure to rural indoor dust may improve allergy prevention.

To address difficulties in the early detection of small gas pipeline leaks, a method is proposed for the image recognition of micropores inside small gas pipelines. First, we design a feature fusion network (Neck) for a small gas pipeline internal micropores identification network model, introducing BiFPN (bi-directional feature pyramid network) into the Neck, and enhancing the micropores feature fusion capability of the network model using cross-scale feature information fusion. Second, we design a classification prediction network (Head) for a small gas pipeline internal micropores identification network model, constructing a small target detection layer in the classification prediction network, and improving the microporosity detection rate of the network model by improving the detection capability for small leakages. Then, micropore datasets are fed into the network model separately to train the model. Finally, comparison and ablation experiments are used to verify the micropore recognition ability of the network model. The experimental results show that the precision of the image recognition method for micropores inside small gas pipelines is 94.7%, the detection rate is 96.6%, and the average precision is 95.5%, which can better realize the early detection of leakages in small gas pipelines.

Starting from the need for emergency rescue information transmission in tunnel engineering accidents, this article focuses on researching and solving the technical problems of information transmission between rescue personnel and trapped personnel after tunnel engineering collapse accidents, before and during the rescue process. The research objects are the information transmission channel and grounding electrode in the earth current field information transmission technology, and the electromagnetic characteristics of the earth medium and the electrical performance of the grounding electrode are studied and analyzed using the electromagnetic simulation software Maxwell based on finite element algorithm, establish a three-dimensional model based on the transmission of current field information of the ground electrode, analyze the effects of the electrode array, electrode depth, and radius on impedance. Research has shown that the impedance of the earth is related to the resistivity of the medium and is not a human-controllable factor. To reduce the contact impedance of an electric dipole antenna, one should start with the contact impedance of the earth electrode. The impedance of the transmitting end is an important factor affecting the efficiency of information transmission; parallel connection of multiple grounding electrodes, increasing the depth of grounding electrode penetration into the soil layer, and increasing the radius between grounding electrode pairs are all effective methods to reduce the contact impedance of electric dipole antennas, thereby improving information transmission capacity. To achieve wireless information transmission through the stratum, by appropriately selecting the operating frequency of electromagnetic waves, a certain distance of signal transmission can be achieved.

To address the issue of low positioning accuracy in unmanned vehicles navigating in obstructed spaces due to easily contaminated navigation measurement information, an improved adaptive federated Kalman filtering INS/GNSS/VNS integrated navigation algorithm is proposed. In this algorithm, an inertial navigation system (INS) serves as the common reference system, and, together with the global navigation satellite system (GNSS) and visual navigation system (VNS), they form the subsystems that together make up the main system. In the event of faulty measurement values in the subsystems, a combination of the residual chi-square and sliding-window averaging methods are used for fault detection to improve the fault tolerance of the integrated navigation algorithm. Additionally, an adaptive sharing factor is proposed to adjust the accuracy of the integrated navigation algorithm based on the accuracy of the sub-filters. Simulation experiments demonstrated that, compared with classic federated Kalman filtering, the proposed algorithm reduced the root mean square errors (RMSEs) of the three-dimensional position by 56.4%, 54.8%, and 43.4% and the root mean square errors of the three-dimensional velocity by 71.0%, 72.1%, and 28.4% in the event of sub-filter faults, effectively solving the problem of low positioning accuracy for unmanned vehicles in obstructed spaces while ensuring the real-time performance of the system.

In order to resolve the problem that the sample of image for internal detection of DN100 buried gas pipeline microleakage is single and difficult to identify, a recognition method of microleakage image of the pipeline internal detection robot is proposed. First, nongenerative data augmentation is used to expand the microleakage images of gas pipelines. Secondly, a generative data augmentation network, Deep Convolutional Wasserstein Generative Adversarial Networks (DCWGANs), is designed to generate microleakage images with different features for detection in the pipeline of gas pipelines to achieve sample diversity of microleakage images of gas pipelines. Then, a bi-directional feature pyramid network (BiFPN) is introduced into You Only Look Once (YOLOv5) to retain more deep feature information by adding cross-scale connecting lines in the feature fusion structure; finally, a small target detection layer is constructed in YOLOv5 so that more shallow feature information can be retained to achieve small-scale leak point recognition. The experimental results show that the precision of this method for microleak identification is 95.04%, the recall rate is 94.86%, the mAP value is 96.31%, and the minimum size of identifiable leaks is 1 mm.

Purpose: Postprostatectomy radiation improves disease control, but limited data exist regarding outcomes, toxicities, and patient-reported quality of life with proton therapy. Method and Materials: The first 102 patients who were enrolled on an outcome tracking protocol between 2006 and 2017 and treated with double-scattered proton therapy after prostatectomy were retrospectively reviewed. Eleven (11%) received adjuvant radiation, while 91 (89%) received salvage radiation. Seventy-four received double-scattered proton therapy to the prostate bed only. Twenty-eight received a double-scattered proton therapy prostate-bed boost after prostate-bed and pelvic-node treatment. Eleven adjuvant patients received a median dose of 66.6 GyRBE (range, 66.0–70.2). Ninety-one salvage patients received a median dose of 70.2 GyRBE (range, 66.0–78.0). Forty-five patients received androgen deprivation therapy for a median 9 months (range, 1–30). Toxicities were scored using Common Terminology Criteria for Adverse Events v4.0 criteria, and patient-reported quality-of-life data were reviewed. Results: The median follow-up was 5.5 years (range, 0.8–11.4 years). Five-year biochemical relapse-free and distant metastases-free survival rates were 72% and 91% for adjuvant patients, 57% and 97% for salvage patients, and 57% and 97% overall. Acute and late grade 3 or higher genitourinary toxicity rates were 1% and 7%. No patients had grade 3 or higher gastrointestinal toxicity. Acute and late grade 2 gastrointestinal toxicities were 5% and 2%. The mean values and SDs of the International Prostate Symptom Score, International Index of Erectile Function, and Expanded Prostate Cancer Index Composite bowel function and bother were 7.5 (SD = 5.9), 10.2 (SD = 8.3), 92.8 (SD = 11.1), and 91.2 (SD = 6.4), respectively, at baseline, and 12.1 (SD = 9.1), 10.1 (SD = 6.7), 87.3 (SD = 18), and 86.7 (SD = 13.8) at the 5-year follow-up. Conclusion: High-dose postprostatectomy proton therapy provides effective long-term biochemical control and freedom from metastasis, with low acute and long-term gastrointestinal and genitourinary toxicity.

The noise suppression of high-resolution range profile (HRRP) is a prerequisite for Geiger-mode of avalanche photodiodes (GM-APD) lidar to achieve precise sensing. However, it is difficult to balance the suppression effect and the integrity of detailed information. Considering this problem, we propose a Bayesian network-based improved loop filter (BNILF) for abnormal noise suppression. Based on the ILF, the Bayesian non-average local filtering model is established to calculate a distance of Pearson distance, which gives the criterion of noise judgment. Furthermore, the block preselection is used to accelerate identify abnormal noise and complete range profile noise suppression. To evaluate the performance of this algorithm, simulation and physical system experiments are carried out. The results show that the proposed algorithm has a better noise suppression effect and a higher detailed information protection ability in comparison with the existing typical approaches.

Abstract Sustainable, conductive, and porous carbon materials are ideal for energy storage materials. In this study, honeycomb‐like carbon materials (HCM) are synthesized via a “salty” thermal treatment of abundant and sustainable coffee extract. Systematic materials characterization indicates that the as‐prepared HCM consists of heteroatoms (N and O, etc.) doped ultra‐thin carbon framework, possesses remarkable specific surface area, and excellent electrical conductivity. Such properties bestow HCM outstanding materials to be the blocking layer for Li‐I2 battery, significantly eliminating the dissolution of I2 in the cathode region and stopping the I2 from shutting to anode compartment. Furthermore, our electrochemical investigation suggests that HCM could incur surface pseudo‐capacitive iodine‐ions charge storage and contribute additional energy storage capacity. As a result, the resultant Li‐I2 battery achieves a robust and highly reversible capacity of 224.5 mAh·g−1 at the rate of 10 C. Even under a high rate of 50 C, the remarkable capacity of the as‐prepared Li‐I2 battery can still be maintained at 120.2 mAh·g−1 after 4000 cycles.

The information transmission mechanism of the ground electrode current field uses a very low-frequency electrical signal, which is applied to the two electrodes driven into the soil layer or the collapsed body of the tunnel to form a current field in the rock layer or soil layer. Signal detection is created via the strong penetration of wireless information transmission. This research focuses on various electromagnetic effects, such as polarization, magnetization, and the transmission of electromagnetic waves under the influence of different media, such as rock, sand, reinforced concrete, and air voids. The influence of these adaptive electromagnetic effects on the transmission of electromagnetic waves is mainly reflected in the reflection, refraction, and attenuation of electromagnetic wave signals. The inhomogeneity of the earth medium, the influence of topographic features, and multi-path transmission all cause signal distortion, fading, or changes in the direction of electromagnetic wave propagation. By studying the three physical quantities of magnetic permeability, permittivity, and conductivity, the electromagnetic characteristics of the earth medium are described to research the information transmission characteristics of the earth electrode current field.

In order to accurately locate personnel in underground spaces, positioning equipment is required to be mounted on wearable equipment. But the wearable inertial personnel positioning equipment moves with personnel and the phenomenon of measurement reference wobble (referred to as moving base) is bound to occur, which leads to inertial measurement errors and makes the positioning accuracy degraded. A neural network-assisted binocular visual-inertial personnel positioning method is proposed to address this problem. Using visual-inertial Simultaneous Localization and Mapping to generate ground truth information (including position, velocity, acceleration data, and gyroscope data), a trained neural network is used to regress 6-dimensional inertial measurement data from the IMU data fragment under the moving base, and a position loss function is constructed based on the regressed inertial data to reduce the inertial measurement error. Finally, using vision as the observation quantity, the point feature and inertial measurement data are tightly coupled to optimize the mechanism to improve the personnel positioning accuracy. Through the actual scene experiment, it is verified that the proposed method can improve the positioning accuracy of personnel. The positioning error of the proposed algorithm is 0.50%D, and it is reduced by 92.20% under the moving base.

Abstract Background The co-occurrence of human immunodeficiency virus (HIV) infection and malaria in humans in endemic areas raises the question of whether one of these infections affects the course of the other. Although epidemiological studies have shown the impact of HIV infection on malaria, the mechanism(s) are not yet fully understood. Using a Chinese rhesus macaque coinfection model with simian immunodeficiency virus (SIV) and Plasmodium cynomolgi (Pc) malaria, we investigated the effect of concurrent SIV infection on the course of malaria and the underlying immunological mechanism(s). Methods We randomly assigned ten Chinese rhesus monkeys to two groups based on body weight and age. The SIV-Pc coinfection animals (S + P group) were infected intravenously with SIVmac251 eight weeks prior to malaria infection, and the control animals (P group) were infected intravenously with only Pc-infected red blood cells. After malaria was cured with chloroquine phosphate, we also initiated a secondary malaria infection that lasted 4 weeks. We monitored body weight, body temperature and parasitemia, measured SIV viral loads, hemoglobin and neopterin, and tracked the CD4+, CD8+, and CD4+ memory subpopulations, Ki67 and apoptosis by flow cytometry. Then, we compared these parameters between the two groups. Results The animals infected with SIV prior to Pc infection exhibited more severe malaria symptoms characterized by longer episodes, higher parasitemia, more severe anemia, greater body weight loss and higher body temperature than the animals infected with Pc alone. Concurrent SIV infection also impaired immune protection against the secondary Pc challenge infection. The coinfected animals showed a reduced B cell response to Pc malaria and produced lower levels of Pc-specific antibodies. In addition, compared to the animals subjected to Pc infection alone, the animals coinfected with SIV and Pc had suppressed total CD4+ T cells, CD4+CD28highCD95high central memory T cells, and CD4+CD28lowCD95− naïve T cells, which may result from the imbalanced immune activation and faster CD4+ T cell turnover in coinfected animals. Conclusions SIV infection aggravates malaria physiologically and immunologically in Chinese rhesus monkeys. This nonhuman primate SIV and Pc malaria coinfection model might be a useful tool for investigating human HIV and malaria coinfection and developing effective therapeutics.

In this paper, we proposed a passive 3D visual sensing technique based on the focal stack and designed the snake robot’s 3D visual sensing prototype. The proposed technique consists of depth reconstruction, all-in-focus imaging and 3D point cloud generation based on the theoretical model of light field reconstruction from the focal stack. The 3D visual sensing prototype was realized by the focal stack acquisition system controlled by the servo motor. In the experiment, the depth map with high precision, all-in-focus image with high spatial resolution as well as the 3D point cloud can be reconstructed in the field-of-view (FOV) by the 3D visual sensing prototype. The proposed technique could be further applied to efficient visual navigation, simultaneous-localization-and-mapping (SLAM) and visual servoing of the robot. Keywords: Visual sensing, Focal stack, Light field imaging, 3D imaging, Snake robot

Aiming at the inherent problems of heading divergence and error accumulation in indoor inertial positioning of pedestrian field, we proposed a new indoor positioning error correction method for pedestrian multi-motions recognition. This method is aimed at pedestrians' seven common indoor movements. Periodically, divide the motion data of the accelerometer in the sensitive-axis-direction (vertical geodetic direction) of MEMS-IMU worn on the pedestrian's waist. And acquire the feature vector through feature extraction by the hybrid-orders fraction domain transformation. The effective features with high identification degree under the different optimal order transformations are mixed and matched. Then, these are sent to each sub-classifier to complete the classification process by the dichotomy and finish the processes of subsequent machine learning. The error correction of the heading angle and positioning is carried out combining with the improved HDE algorithm, the innovative floor constraints' method, and the motion states' transition correction technique. The final indoor positioning experiment results show that the classification effect of this motion detection method is better than the traditional methods'. The average classification accuracy can reach up to 97%. And the method reduces the computing requirements for hardware. By using the floor constraint method, the vertical height difference can achieve the effect of complete reset of the origin. The trajectory lines of the movement in the same floor are well displayed. At the same time, the best horizontal error positioning result is only 1.72 m during the total travel distance of 412.40 m (TTD ≈ 0.42%).

Accurate measurement of high spinning projectiles' attitude is the basis of guidance and control. In order to reduce the attitude measurement error and improve the attitude update rate, a magnetometer-based phase shifting ratio method is proposed in this paper. This method does not introduce additional installation errors as the existing methods, simplifies the calibration of the extreme value ratio-pitch angle curve, and makes full use of the measurement data of the sensors. The attitude update is synchronized with the magnetometer output without using the local geomagnetic information. Simultaneously, the local geomagnetic errors are avoided. The results of numerical simulation and semi-physical simulation experiments show that compared with the three orthogonal ratio method and the crest and trough method, the proposed algorithm in this paper can increase the attitude update rate by more than 2 times and the attitude calculation accuracy can be enhanced by 30%.

Aiming at the problem of attitude angular motion coupling of a high-spinning rigid body, the model of the compound regular precession and the random angular motion is constructed by studying the angular motion characteristics of the high-spinning rigid body. This paper presents a new decoupling method with least squares angular rate zero-crossing detection. This method can estimate the coupling parameters in the model by estimating the angular motion period, and then, it extracts the real angular velocity information. In order to improve the attitude solution accuracy, a new four-subsample quaternion attitude algorithm is proposed by combining the angular velocity polynomial fitting and the attitude quaternion high-order Taylor series expansion. The self-developed high dynamic gyro and Missile-borne computer and simulation software are used to verify the attitude angle resolution accuracy between the traditional method and the new method proposed in this paper. The results show that the method is superior to the traditional algorithm, and increase by an order of magnitude. Finally, the flight test with the high dynamic gyro and Missile-borne computer is carried out to verify the real-time decoupling and attitude angle real-time solving ability of the proposed algorithm in the flight test.

The metal shell vibratory gyro is a branch of Coriolis vibratory gyro, which has the advantage of overload resistance, simplify structure, low cost, wide range and long life. This paper focuses on multi-surface metal resonator. It is important that the eigenvalue analysis of multi-surface of hemisphere, cylinder and hyperbolic. Through analysis multi-surface characteristic, it presents a novel orthogonal curvilinear coordinate used machine error factor based on the traditional coordinate, which realizes boundary linear. We analyze its natural vibration characteristics, research on basic model distribution and built mode shape function of resonator; deeply research on dynamics characteristics of resonator under the condition of angular rate input, establish dynamics equation of multi-surface fusion metal shell vibratory gyroscope based on thin shell mechanics theory of elastic mechanics, solve out the eigenvalue of the resonator, and we also analyze this eigenvalue characteristics to lay the foundation of the follow-up study of the theory of the metal shell vibratory gyroscope. We test the gyro's temperature performance on the last. Finally, we test on the metal shell vibratory gyroscope, the ranges to ±3600°/s, zero-bias stability is 7.862°/h (25 °C), angular random walk is 1.487°/h1/2.

Conventional attitude algorithms have been improved for many years, but they still have attitude updating errors due to the coupling in the complicated angular motion of spinning bodies. A real-time angular motion decoupling and attitude updating method assisted by satellite navigation data is proposed in this paper. A compositive model of angular motion for spinning bodies is built to understand and analyze the trait of angular velocity. A detailed process of angular motion decoupling is addressed with the help of satellite navigation data, including a backward decoupling process and a forward decoupling angular process, to estimate angular velocity to guarantee real-time ability. A real-time attitude updating algorithm is presented in detail for determining the real attitude of spinning bodies, and the updating process of coning attitude based on rotation vector is provided. Simulations are carried out to show the coupling effect of angular motion on the conventional attitude algorithm and verify the validity of the proposed method, and flight data are used to verify the availability of engineering application. Results show that the angular motion is decoupled and attitude accuracy is improved successfully.

Aiming at the problem of the weak dynamic performance of the gradient descent method in the attitude and heading reference system, the susceptibility to the interference of accelerometers and magnetometers, and the complex calculation of the nonlinear Kalman Filter method, an extended Kalman filter suitable for a low-cost magnetic, angular rate, and gravity (MARG) sensor system is proposed. The method proposed in this paper is a combination of a two-stage gradient descent algorithm and the extended Kalman filter (GDEKF). First, the accelerometer and magnetometer are used to correct the attitude angle according to the two-stage gradient descent algorithm. The obtained attitude quaternion is combined with the gyroscope measurement value as the observation vector of EKF and the calculated attitude of the gyroscope and the bias of the gyroscope are corrected. The elimination of the bias of the gyroscope can further improve the stability of the attitude observation results. Finally, the MARG sensor system was designed for mathematical model simulation and hardware-in-the-loop simulation to verify the performance of the filter. The results show that compared with the gradient descent method, it has better anti-interference performance and dynamic performance, and better measurement accuracy than the extended Kalman filter.

We consider the channel estimation of millimeter wave (mmWave) multiple-input multiple-output systems, where both the transmitter and receiver adopt hybrid beamforming structure. Due to the spatial sparsity of the mmWave channel, it can be reconstructed by estimating the direction and gain of the paths. Leveraging this feature, we propose a channel estimation algorithm based on subspace fitting to estimate the path directions, and the path gains are obtained using the least squares method. However, similar to the most existing mmWave channel estimation schemes, the proposed algorithm requires a two-dimensional search in candidate angle space, which is very complicated. In order to reduce the computational complexity, we develop a low-complexity channel estimation algorithm using the orthogonal matching pursuit (OMP) method, which significantly reduces the computational complexity. However, when the paths are strongly correlated, the channel estimation accuracy will decrease. To overcome this defect, we further develop a low-complexity method based on subspace fitting. This algorithm makes a trade-off between the computational complexity and channel estimation accuracy. Furthermore, the pilot beam pattern for different hybrid beamforming structure is designed using infinitely and quantized phase shifters to improve the signal-to-noise ratio of the pilot signals. In addition, the proposed channel estimation methods can also be used in the multi-user scenario. Simulation results demonstrate that the proposed subspace fitting method outperforms the existing methods when the angular resolution is the same. Meanwhile, the low-complexity OMP and subspace fitting methods have a good performance in single path scenario when compared to subspace fitting method, even if the computation complexity is lower. Moreover, the performance of the low-complexity subspace fitting method is close to the subspace fitting method.

The light field can be applied to computational imaging methods, such as digital refocusing, depth reconstruction, and all-in-focus imaging. In this paper, the affine Radon transform of generating the focal stack by the light field is proposed. Then, we derive the inverse formula of the affine Radon transform for reconstructing the light field from the focal stack. We analyze the ill-posedness of the reconstruction problem by the inversion formula and the incompleteness of the focal stack data. The inversion formula reveals the instability of the solution. The focal stack can be regarded as the incomplete data for light field reconstruction in the spatial domain, while it corresponds to the limited support of light field in the Fourier domain. The numerical solution of light field reconstruction is realized by approximating the inverse of the affine Radon transform. Based on the approximated inverse affine Radon transform of light field reconstruction, the high-precision light field data reconstruction method and the computational imaging method can be established via the focal stack data. The experimental results show that the high-precision light field can be reconstructed from focal stack based on the approximated inverse affine Radon transform.

Abstract Background Lipoic acid is a cofactor for α-keto acid dehydrogenase system that is involved in the central energy metabolism. In the apicomplexan parasite, Plasmodium, lipoic acid protein ligase 1 (LplA1) and LplA2 catalyse the ligation of acquired lipoic acid to the dehydrogenase complexes in the mitochondrion. The enzymes LipB and LipA mediate lipoic acid synthesis and ligation to the enzymes in the apicoplast. These enzymes in the lipoic acid metabolism machinery have been shown to play important roles in the biology of Plasmodium parasites, but the relationship between the enzymes is not fully elucidated. Methods We used an anhydrotetracycline (ATc)-inducible transcription system to generate transgenic P. berghei parasites in which the lplA1 gene was conditionally knocked out (LplA1-cKO). Phenotypic changes and the lplA1 and lplA2 gene expression profiles of cloned LplA1-cKO parasites were analysed. Results LplA1-cKO parasites showed severely impaired growth in vivo in the first 8 days of infection, and retarded blood-stage development in vitro, in the absence of ATc. However, these parasites resumed viability in the late stage of infection and mounted high levels of parasitemia leading to the death of the hosts. Although lplA1 mRNA expression was regulated tightly by ATc during the whole course of infection, lplA2 mRNA expression was significantly increased in the late stage of infection only in the LplA1-cKO parasites that were not exposed to ATc. Conclusions The lplA2 gene can be activated as an alternative pathway to compensate for the loss of LplA1 activity and to maintain lipoic acid metabolism.

This paper studies the measurement of motion parameters of a parachute scanning platform. The movement of a parachute scanning platform has fast rotational velocity and a complex attitude. Therefore, traditional measurement methods cannot measure the motion parameters accurately, and thus fail to satisfy the requirements for the measurement of parachute scanning platform motion parameters. In order to solve these problems, a method for measuring the motion parameters of a parachute scanning platform based on a combination of magnetic and inertial sensors is proposed in this paper. First, scanning motion characteristics of a parachute-terminal-sensitive projectile are analyzed. Next, a high-precision parachute scanning platform attitude measurement device is designed to obtain the data of magnetic and inertial sensors. Then the extended Kalman filter is used to filter and observe errors. The scanning angle, the scanning angle velocity, the falling velocity, and the 2D scanning attitude are obtained. Finally, the accuracy and feasibility of the algorithm are analyzed and validated by MATLAB simulation, semi-physical simulation, and airdrop experiments. The presented research results can provide helpful references for the design and analysis of parachute scanning platforms, which can reduce development time and cost.

A bell-shaped vibratory angular velocity gyro (BVG), inspired by the Chinese traditional bell, is a type of axisymmetric shell resonator gyroscope. This paper focuses on development of an error model and compensation of the BVG. A dynamic equation is firstly established, based on a study of the BVG working mechanism. This equation is then used to evaluate the relationship between the angular rate output signal and bell-shaped resonator character, analyze the influence of the main error sources and set up an error model for the BVG. The error sources are classified from the error propagation characteristics, and the compensation method is presented based on the error model. Finally, using the error model and compensation method, the BVG is calibrated experimentally including rough compensation, temperature and bias compensation, scale factor compensation and noise filter. The experimentally obtained bias instability is from 20.5°/h to 4.7°/h, the random walk is from 2.8°/h1/2 to 0.7°/h1/2 and the nonlinearity is from 0.2% to 0.03%. Based on the error compensation, it is shown that there is a good linear relationship between the sensing signal and the angular velocity, suggesting that the BVG is a good candidate for the field of low and medium rotational speed measurement.

A bell-shaped vibratory angular rate gyro, which is inspired by the Chinese traditional bell, is a kind of axisymmetric shell resonator gyroscope. Its sensitive element is a vibratory-like Chinese traditional bell, using a piezoelectric element on the wall of the vibrator to detect the standing wave’s precession to solve the input angular rate. This work mainly studies the circuit system of a bell-shaped vibratory angular rate gyro. It discusses the process of circuit system design, analysis and experiment, in detail, providing the foundation to develop a bell-shaped vibratory angular rate gyro. Since the bell-shaped resonator’s curved structure has the characteristics of large noise in the piezoelectric signal and large harmonics, this paper analyzes its working and signal detection method, then gives the whole plan of the circuit system, including the drive module, the detection module and the control loop. It also studies every part of the whole system, gives a detailed design and analysis process and proves part of the circuit system using digital simulation. At the end of the article, the test result of the circuit system shows that it can remove the disadvantages of the curved structure having large noise in the piezoelectric signal and large harmonics and is more effective at solving the input angular rate.

With the aim of designing an action detection method on artificial knee, a new time−frequency feature extraction method was proposed. The inertial data were extracted periodically using the microelectromechanical systems (MEMS) inertial measurement unit (IMU) on the prosthesis, and the features were extracted from the inertial data after fractional Fourier transform (FRFT). Then, a feature vector composed of eight features was constructed. The transformation results of these features after FRFT with different orders were analyzed, and the dimensions of the feature vector were reduced. The classification effects of different features and different orders are analyzed, according to which order and feature of each sub-classifier were designed. Finally, according to the experiment with the prototype, the method proposed above can reduce the requirements of hardware calculation and has a better classification effect. The accuracies of each sub-classifier are 95.05%, 95.38%, 91.43%, and 89.39%, respectively; the precisions are 78.43%, 98.36%, 98.36%, and 93.41%, respectively; and the recalls are 100%, 93.26%, 86.96%, and 86.68%, respectively.

A high-precision navigation system is required for an unmanned vehicle, and the high-precision sensor is expensive. A low-cost, high-precision, dual-antenna Global Navigation Satellite System/Micro-electromechanical Systems-Inertial Navigation System (GNSS/MINS) combination method is proposed. The GNSS with dual antennas provides velocity, position, and attitude angle information as the measurement information is combined with the MINS. By increasing the heading angle, pitch angle, velocity, the accuracy of the integrated system is improved. The Extended Kalman Filtering (EKF) integrated algorithm simulation is designed to verify the feasibility and is realized based on the Field Programmable Gate Array and Advanced RISC Machine (ARM+FPGA) system. Static and dynamic tests were performed using the Synchronous Position, Attitude and Navigation (SPAN-CPT) as a reference system. The results show that the velocity, position, and attitude angle accuracy were improved. The yaw angle and pitch angle accuracy were 0.2° Root Mean Square (RMS) and 0.3° RMS, respectively. The method can be used as a navigation system for the unmanned vehicle.

A low cost, high precision hollow structure MEMS IMU has been developed to measure the roll angular rate of a high-spinning projectile. The hollow MEMS IMU is realized by designing the scheme of non-centroid configuration of multiple accelerometers. Two dual-axis accelerometers are respectively mounted on the pitch axis and the yaw axis away from the center of mass of the high-spinning projectile. Three single-axis gyros are mounted orthogonal to each other to measure the angular rates, respectively. The roll gyro is not only used to judge the spinning direction, but also to measure and compensate for the low rotation speed of the high-spinning projectile. In order to improve the measurement accuracy of the sensor, the sensor output error is modeled and calibrated by the least square method. By analyzing the influence of noise statistical characteristics on angular rate solution accuracy, an adaptive unscented Kalman filter (AUKF) algorithm is proposed, which has a higher estimation accuracy than UKF algorithm. The feasibility of the method is verified by numerical simulation. By using the MEMS IMU device to build a semi-physical simulation platform, the solution accuracy of the angular rate is analyzed by simulating different rotation speeds of the projectile. Finally, the flight test is carried out on the rocket projectile with the hollow MEMS IMU. The test results show that the hollow MEMS IMU is reasonable and feasible, and it can calculate the roll angular rate in real time. Therefore, the hollow MEMS IMU designed in this paper has certain engineering application value for high-spinning projectiles.

The bell-shaped vibratory angular rate gyro (abbreviated as BVG) is a novel shell vibratory gyroscope, which is inspired by the Chinese traditional bell. It sensitizes angular velocity through the standing wave precession effect. The bell-shaped resonator is a core component of the BVG and looks like the millimeter-grade Chinese traditional bell, such as QianLong Bell and Yongle Bell. It is made of Ni43CrTi, which is a constant modulus alloy. The exciting element, control element and detection element are uniformly distributed and attached to the resonator, respectively. This work presents the design, analysis and experimentation on the BVG. It is most important to analyze the vibratory character of the bell-shaped resonator. The strain equation, internal force and the resonator's equilibrium differential equation are derived in the orthogonal curvilinear coordinate system. When the input angular velocity is existent on the sensitive axis, an analysis of the vibratory character is performed using the theory of thin shells. On this basis, the mode shape function and the simplified second order normal vibration mode dynamical equation are obtained. The coriolis coupling relationship about the primary mode and secondary mode is established. The methods of the signal processing and control loop are presented. Analyzing the impact resistance property of the bell-shaped resonator, which is compared with other shell resonators using the Finite Element Method, demonstrates that BVG has the advantage of a better impact resistance property. A reasonable means of installation and a prototypal gyro are designed. The gyroscopic effect of the BVG is characterized through experiments. Experimental results show that the BVG has not only the advantages of low cost, low power, long work life, high sensitivity, and so on, but, also, of a simple structure and a better impact resistance property for low and medium angular velocity measurements.

Bell-shaped vibratory angular rate gyro (abbreviated as BVG) is a new type Coriolis vibratory gyro that was inspired by Chinese traditional clocks. The resonator fuses based on a variable thickness axisymmetric multicurved surface shell. Its characteristics can directly influence the performance of BVG. The BVG structure not only has capabilities of bearing high overload, high impact and, compared with the tuning fork, vibrating beam, shell and a comb structure, but also a higher frequency to overcome the influence of the disturbance of the exterior environment than the same sized hemispherical resonator gyroscope (HRG) and the traditional cylinder vibratory gyroscope. It can be widely applied in high dynamic low precision angular rate measurement occasions. The main work is as follows: the issue mainly analyzes the structure and basic principle, and investigates the bell-shaped resonator’s mathematical model. The reasonable structural parameters are obtained from finite element analysis and an intelligent platform. Using the current solid vibration gyro theory analyzes the structural characteristics and principles of BVG. The bell-shaped resonator is simplified as a paraboloid of the revolution mechanical model, which has a fixed closed end and a free opened end. It obtains the natural frequency and vibration modes based on the theory of elasticity. The structural parameters are obtained from the orthogonal method by the research on the structural parameters of the resonator analysis. It obtains the modal analysis, stress analysis and impact analysis with the chosen parameters. Finally, using the turntable experiment verifies the gyro effect of the BVG.

A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot’s motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU). First, it studies the snake robot’s motion characteristics, builds the kinematics model, and then analyses the motion constraint characteristics and motion error propagation properties. Second, it explores the snake robot’s navigation layout, proposes a constraint criterion and the fixed relationship, and makes zero-state constraints based on the motion features and control modes of a snake robot. Finally, it realizes autonomous navigation positioning based on the Extended-Kalman-Filter (EKF) position estimation method under the constraints of its motion characteristics. With the self-developed snake robot, the test verifies the proposed method, and the position error is less than 5% of Total-Traveled-Distance (TDD). In a short-distance environment, this method is able to meet the requirements of a snake robot in order to perform autonomous navigation and positioning in traditional applications and can be extended to other familiar multi-link robots.

Due to the fact that attitude error of vehicles has an intense trend of divergence when vehicles undergo worsening coning environment, in this paper, the model of dynamic coning environment is derived firstly. Then, through investigation of the effect on Euler attitude algorithm for the equivalency of traditional attitude algorithm, it is found that attitude error is actually the roll angle error including drifting error and oscillating error, which is induced directly by dynamic coning environment and further affects the pitch angle and yaw angle through transferring. Based on definition of the cone frame and cone attitude, a cone algorithm is proposed by rotation relationship to calculate cone attitude, and the relationship between cone attitude and Euler attitude of spinning vehicle is established. Through numerical simulations with different conditions of dynamic coning environment, it is shown that the induced error of Euler attitude fluctuates by the variation of precession and nutation, especially by that of nutation, and the oscillating frequency of roll angle error is twice that of pitch angle error and yaw angle error. In addition, the rotation angle is more competent to describe the spinning process of vehicles under coning environment than Euler angle gamma, and the real pitch angle and yaw angle are calculated finally.

Due to power-after-launch mode of guided munitions of high rolling speed, initial attitude of munitions cannot be determined accurately, and this makes it difficult for navigation and control system to work effectively and validly. An in-flight self-alignment method aided by geomagnetism that includes a fast in-flight coarse alignment method and an in-flight alignment model based on Kalman theory is proposed in this paper. Firstly a fast in-flight coarse alignment method is developed by using gyros, magnetic sensors, and trajectory angles. Then, an in-flight alignment model is derived by investigation of the measurement errors and attitude errors, which regards attitude errors as state variables and geomagnetic components in navigation frame as observed variables. Finally, fight data of a spinning projectile is used to verify the performance of the in-flight self-alignment method. The satisfying results show that (1) the precision of coarse alignment can attain below 5°; (2) the attitude errors by in-flight alignment model converge to 24′ at early of the latter half of the flight; (3) the in-flight alignment model based on Kalman theory has better adaptability, and show satisfying performance.

Immunosuppression associated with infections of nematode parasites has been documented. Cysteine protease inhibitor (CPI) released by the nematode parasites is identified as one of the major modulators of host immune response. In this report, we demonstrated that the recombinant CPI protein of Ascaris lumbricoides (Al-CPI) strongly inhibited the activities of cathepsin L, C, S, and showed weaker effect to cathepsin B. Crystal structure of Al-CPI was determined to 2.1 Å resolution. Two segments of Al-CPI, loop 1 and loop 2, were proposed as the key structure motifs responsible for Al-CPI binding with proteases and its inhibitory activity. Mutations at loop 1 and loop 2 abrogated the protease inhibition activity to various extents. These results provide the molecular insight into the interaction between the nematode parasite and its host and will facilitate the development of anthelmintic agents or design of anti-autoimmune disease drugs.