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Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems. In a complex traffic environment, the signal of the Global Navigation Satellite System (GNSS) will be blocked, leading to inaccurate vehicle positioning. To ensure the security of automatic electric campus vehicles, this study is based on the Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain (LEGO-LOAM) algorithm with a monocular vision system added. An algorithm framework based on Lidar-IMU-Camera (Lidar means light detection and ranging) fusion was proposed. A lightweight monocular vision odometer model was used, and the LEGO-LOAM system was employed to initialize monocular vision. The visual odometer information was taken as the initial value of the laser odometer. At the back-end opti9mization phase error state, the Kalman filtering fusion algorithm was employed to fuse the visual odometer and LEGO-LOAM system for positioning. The visual word bag model was applied to perform loopback detection. Taking the test results into account, the laser radar loopback detection was further optimized, reducing the accumulated positioning error. The real car experiment results showed that our algorithm could improve the mapping quality and positioning accuracy in the campus environment. The Lidar-IMU-Camera algorithm framework was verified on the Hong Kong city dataset UrbanNav. Compared with the LEGO-LOAM algorithm, the results show that the proposed algorithm can effectively reduce map drift, improve map resolution, and output more accurate driving trajectory information.

Abstract Background Proper flowering time is important for the growth and development of plants, and both too early and too late flowering impose strong negative influences on plant adaptation and seed yield. Thus, it is vitally important to study the mechanism underlying flowering time control in plants. In a previous study by the authors, genome-wide association analysis was used to screen the candidate gene SISTER OF FCA (SSF) that regulates FLOWERING LOCUS C (FLC), a central gene encoding a flowering suppressor in Arabidopsis thaliana. Results SSF physically interacts with Protein arginine methyltransferase 5 (PRMT5, SKB1). Subcellular co—localization analysis showed that SSF and SKB1 interact in the nucleus. Genetically, SSF and SKB1 exist in the same regulatory pathway that controls FLC expression. Furthermore, RNA-sequencing analysis showed that both SSF and SKB1 regulate certain common pathways. Conclusions This study shows that PRMT5 interacts with SSF, thus controlling FLC expression and facilitating flowering time control.

Abstract Through pumping a spin current from ferromagnet into heavy metal (HM) via magnetization precession, parts of the injected spins are in-plane rotated by the lattice vibration, namely acoustic spin rotation (ASR), which manifests itself as an inverse spin Hall voltage in HM with an additional 90° difference in angular dependency. When reversing the stacking order of bilayer with a counter-propagating spin current or using HMs with an opposite spin Hall angle, such ASR voltage shows the same sign, strongly suggesting that ASR changes the rotation direction due to interface spin-orbit interaction. With the drift-diffusion model of spin transport, we quantify the efficiency of ASR up to 30%. The finding of ASR endows the acoustic device with an ability to manipulate spin, and further reveals a new spin-orbit coupling between spin current and lattice vibration.

Photodynamic therapy (PDT) has limited effects in treating metastatic breast cancer. Immune checkpoints can deplete the function of immune cells; however, the expression of immune checkpoints after PDT is unclear. This study investigates whether the limited efficacy of PDT is due to upregulated immune checkpoints and tries to combine the PDT and immune checkpoint inhibitor to observe the efficacy. A metastatic breast cancer model was treated by PDT mediated by hematoporphyrin derivatives (HpD-PDT). The anti-tumor effect of HpD-PDT was observed, as well as CD4[Formula: see text]T, CD8[Formula: see text]T and calreticulin (CRT) by immunohistochemistry and immunofluorescence. Immune checkpoints on T cells were analyzed by flow cytometry after HpD-PDT. When combining PDT with immune checkpoint inhibitors, the antitumor effect and immune effect were assessed. For HpD-PDT at 100[Formula: see text]mW/cm2 and 40, 60 and 80[Formula: see text]J/cm2, primary tumors were suppressed and CD4[Formula: see text]T, CD8[Formula: see text]T and CRT were elevated; however, distant tumors couldn’t be inhibited and survival could not be prolonged. Immune checkpoints on T cells, especially PD1 and LAG-3 after HpD-PDT, were upregulated, which may explain the reason for the limited HpD-PDT effect. After PDT combined with anti-PD1 antibody, but not with anti-LAG-3 antibody, both the primary and distant tumors were significantly inhibited and the survival time was prolonged, additionally, CD4[Formula: see text]T, CD8[Formula: see text]T, IFN-[Formula: see text]CD4[Formula: see text]T and TNF-[Formula: see text]CD4[Formula: see text]T cells were significantly increased compared with HpD-PDT. HpD-PDT could not combat metastatic breast cancer. PD1 and LAG-3 were upregulated after HpD-PDT. Anti-PD1 antibody, but not anti-LAG-3 antibody, could augment the antitumor effect of HpD-PDT for treating metastatic breast cancer.

Inflammatory bowel disease (IBD) is a nonspecific chronic inflammatory disease resulting from an immune disorder in the intestine that is prone to relapse and incurable. The understanding of the pathogenesis of IBD remains unclear. In this study, we found that ace (angiotensin-converting enzyme), expressed abundantly in the intestine, plays an important role in IBD. The deletion of ace in zebrafish caused intestinal inflammation with increased expression of the inflammatory marker genes interleukin 1 beta (il1b), matrix metallopeptidase 9 (mmp9), myeloid-specific peroxidase (mpx), leukocyte cell-derived chemotaxin-2-like (lect2l), and chemokine (C-X-C motif) ligand 8b (cxcl8b). Moreover, the secretion of mucus in the ace−/− mutants was significantly higher than that in the wild-type zebrafish, validating the phenotype of intestinal inflammation. This was further confirmed by the IBD model constructed using dextran sodium sulfate (DSS), in which the mutant zebrafish had a higher susceptibility to enteritis. Our study reveals the role of ace in intestinal homeostasis, providing a new target for potential therapeutic interventions.

Abstract Background The purpose of our study was to explore the sonographic characteristics of fibromas of the tendon sheath of the hand and wrist and to evaluate the value of high frequency ultrasound in the diagnosis of FTS. Methods We retrospectively reviewed the sonography of 42 patients with surgically proven FTS, including one with a relapsing tumor (43 lesions in total). The location, size, distribution, relationship with the surrounding tissue, two-dimensional gray-scale sonographic appearance and internal color blood flow of all lesions were analysed. Results The maximum diameter ranged from 0.4 to 2.8 cm, with an average of 1.5 ± 0.6 cm. Twenty-eight lesions (65%) were associated with an adjacent tendon, while the other 15 lesions (35%) were next to the joint. Spindle or oval lesions were common, followed by irregular shape. The nodules with clear boundaries were hypoechoic and had posterior echo enhancement. Thirty-seven lesions (86%) were homogeneous, while 6 lesions (14%) had cystic components with no echo inside. Seventeen lesions (40%) had a large amount of blood flow. Nine lesions (20%) had a small amount of blood flow. The other 17 lesions (40%) had no significant blood flow. Conclusions The diagnosis of fibroma of the tendon sheath can be considered when ultrasound examination reveals a focal nodular mass adjacent to a tendon sheath with homogeneous hypoechogenicity and no or small or large amounts of blood flow.

Abstract Phytoplasmas are small bacterial parasites that lack cell walls and are transmitted in a persistent-propagative manner by insect vectors. However, detailed multiplication patterns and movements of phytoplasmas within host plant and insect vector remain elusive. In this study, a specific antibody against the immunodominant membrane protein (Imp) of rice orange leaf phytoplasma (ROLP) was generated and subjected to the frozen section immune gold labeling assay, immune gold labeling microscopy, and immune fluorescence labeling assay to investigate how ROLP enters, propagates, and spreads in rice and its leafhopper vector Recilia dorsalis at the ultrastructural level. During acquisition and transmission by insect vectors, ROLPs could squeeze and penetrate the multiple membrane/tissue barriers such as microvilli, apical plasmalemma, and basal lamina in the intestines or salivary glands by endocytosis- and exocytosis-like mechanism. Furthermore, ROLP infection is restricted to the type IV and V cells of salivary glands. In contrast to the classical binary fission used by most bacteria, electron microscopy reveals that ROLP exploits an asymmetrical budding strategy to replicate in plant hosts and insect vectors. In this process, a cellular protrusion of ROLP forms a bud to reproduce the offspring by fission at the junction between the bud and the ROLP main body. These results clarify the infection characteristics of ROLP in rice and R. dorsalis, which will help guide the formulation of ROLP prevention and control strategies.

The purpose of semi-supervised video object segmentation (VOS) is to predict and generate object masks in subsequent video frames after being provided with the initial frame’s object mask. Currently, mainstream methods leverage historical frame information for enhancing the network’s performance. However, this approach faces the following issues: (1) They often overlook important shape information, leading to decreased accuracy in segmenting object-edge areas. (2) They often use pixel-level motion estimation to guide the matching for addressing distractor objects. However, this brings heavy computation costs and struggle against occlusion or fast/blurry motion. For the first problem, this paper introduces an object shape extraction module that exploits both the high-level and low-level features to obtain object shape information, by which the shape information can be used to further refine the predicted masks. For the second problem, this paper introduces a novel object-level motion prediction module, in which it stores the representative motion features during the training stage, and predicts the object motion by retrieving them during the inference stage. We evaluate our method on benchmark datasets compared with recent state-of-the-art methods, and the results demonstrate the effectiveness of the proposed method.

Peptide heterodimers are prevalent in nature, which are not only functional macromolecules but molecular tools for chemical and synthetic biology. Here the authors report de novo design and directed folding of peptide heterodimers crosslinked through multiple disulfide bonds, which can be explored as chemical tools for orthogonal labeling of proteins and preparing protein hybrids.

Photodynamic therapy (PDT) not only destroys tumor cells directly but also induced anti-tumor immune response through damage-associated molecular patterns (DAMPs). It is reported that anti-tumor response was associated with light dose and photosensitizer used in PDT. In this study, 4T1 tumor cells were implanted on both the right and left flanks of mice. Only the right tumor was treated by HpD-PDT, while the left tumor was not irradiated. The anti-tumor immune response induced by HpD-PDT was investigated. The expression of DAMPs and co-stimulatory molecules induced by HpD-PDT were tested by immunofluorescence and flow cytometry in vivo. Different light doses of PDT were designed to treat 4T1 cells. The killing effect was assessed by CCK-8 kit and apoptosis kit. The expression of DAMPs on 4T1 cells after HpD-PDT were evaluated by flow cytometry, western blot and ATP kit. This study showed that CD4[Formula: see text]T, CD8[Formula: see text]T and the production of IFN-[Formula: see text] were increased significantly on day 10 in right-tumor after PDT treatment compared with control group. HpD-PDT enhanced the expression of calreticulin (CRT) on tumor tissue. Importantly, co-stimulatory molecular OX-40 and 4-1BB were elevated on CD8[Formula: see text]T cells. In vitro, immunogenic death of 4T1 cells was induced after PDT. Besides, the expression of DAMPs increased with the increasing of energy density. This study indicates that anti-tumor immune effect was induced by HpD-PDT. The knowledge of the involvement of CRT, ATP and co-stimulatory molecules uncovers important mechanistic insight into the anti-tumor immunogenicity. It was the first time that co-stimulatory molecules were investigated and found to elevate after PDT.

Modern research has proved that the main medicinal component of Rhodiola crenulata, which has a wide range of medicinal value, is its secondary metabolite salidroside. The MYB transcription factor family is widely involved in biosynthesis of second metabolism and other roles in the stress response in plants, so a genome-wide identification and analysis for this family in R. crenulata is worth conducting. In this research, genome-wide analysis identified 139 MYB genes based on conserved domains in the R. crenulata genome, and 137 genes were used to construct a phylogenetic tree and modified with expression files to reveal evolutionary characteristics. Physical and chemical characteristics, gene structure, and conserved motif analysis were also used to further analyze RcMYBs. Additionally, cis-acting elements related to transcription, hormone, and MYB binding were found in the promoter region of the selected RcMYBs. Four RcMYBs were cloned, sequenced, and their gene expression pattern was analyzed for further analysis of their functions. The research results lay the foundation for further research on the function of RcMYB and R. crenulata.

With the continuous improvement of substation automation, the number of communication equipment has risen sharply, the network topology is more complicated, and the problem of unable to locate the fault of process-level communication networks quickly and accurately has become more and more prominent. Under this background, to improve the maintenance efficiency of process-level communication networks in the smart substation, this article proposes a method for fault location of process-level communication networks based on deep neural networks. Based on the redundant monitoring of the fault state, the fault feature information of different monitoring nodes in the message transmission process is analyzed, and the characterization method of the fault feature information is proposed accordingly. Based on the emergence principle, it realizes the automatic generation of fault samples according to the physical connection, logical connection, and message subscription relationship of process-level communication networks. Combined with the training rules in deep learning theory, a fault location model of process-level communication networks based on deep neural networks is established, and the real-time location steps are given. Taking the process-level communication network of a typical 110kV smart substation as an example, simulations verify the effectiveness and accuracy of the proposed fault location method in single fault environments and multiple fault environments. Besides, accurate results can be obtained even when the fault feature information is wrong or missing, and the anti-interference ability is excellent.

Off-road intelligent vehicle is an important application about Internet of Vehicles technology used in the transportation field, and the front obstacle recognition method is the key technology for off-road intelligent vehicle. In this paper, based on smart data aggregation inspired paradigm of IoT applications, we mainly study perception technology in vehicle networking by using image data and one symmetrical speeded-up robust features detector (SURF). By considering symmetry and image data aggregation, we found that data aggregation had the ability of providing global information for Internet of Vehicles systems. After we have built the experiment platform, the experiment results showed that this method is faster than Scale-Invariant Feature Transform algorithm in this case, which can satisfy the water detection accuracy and the real-time requirement. So, this method is effective for the water images detection with great symmetry to off-road intelligent vehicle, and it also gives a useful reference about environment perception technology and smart data aggregation inspired paradigm used in future Internet of Vehicles, intelligent vehicle, and traffic safety applications.

In order to adhere to the wall stably in an underwater environment, a vortex suction cup that injects high-pressure water inside via two axisymmetrically side-distributed inlets to create a negative pressure area in the center is the necessary component for the underwater climbing robot (UCR). However, the suction force of this vortex suction cup is reduced and periodically unstable due to unstable cavitation. The aim of this paper is to propose a cavitation reduction optimization method for vortex suction cups and to verify the effectiveness of the optimization. Analyses of this vortex flow, including streamlines, pressure, and cavitation number fluctuations, were carried out by the introduced computational fluid dynamics (CFD) simulating methods based on the multiphase RNG k−ε model to study the periodic fluctuations of the suction force of the original suction cup and the optimized ones. Force measurement and vortex observation experiments were conducted to compare the suction force of the original vortex suction cup and the optimized suction cup, as well as the cavitation and pressure fluctuation phenomenon. Results of simulation and experiments prove the existence of the effect of vortex cavitation on the suction performance and verify the rationality of optimization as well.

The building density of Central Business District (CBD) is usually high. Land for a bus terminal is insufficient. In this situation, passengers in CBD have to walk far to take a bus, or take a long time to wait for a taxi. To solve this problem, this paper proposes an indirect approach: the design of a circle line of shuttle bus as a dynamic bus terminal in CBD. The shuttle bus can deliver people to the bus station through a circle line. This approach not only reduces the traffic pressure in CBD, but also saves travel time of the passenger. A bi-objective model is proposed to design a circle line of a shuttle bus for CBD. The problem is solved by non-dominated sorting genetic algorithm (NSGA-II). Furthermore, the Dalian city in China has been chosen as the case study to test the proposed method. The results indicate that the method is effective for circle line optimization of shuttle bus in central business district without a bus terminal.

Continuously cultured cell lines derived from planthopper and leafhopper have greatly facilitated the investigation of rice viruses transmitted by these insects. However, the lack of a suitable transient expression vector has limited their utility. Here, by cloning and analyzing the promoter sequence of the gene encoding cytoplasmic actin from the leafhopper Nephotettix cincticeps, we successfully developed the first efficient transient expression vector for cultured leafhopper cells, which can also be used to express exogenous proteins in other insect culture cell lines, including those derived from Recilia dorsalis leafhopper and Spodoptera frugiperda (Sf9). Furthermore, insertion of the Hr5 viral enhancer element and knockdown of the endogenous Dicer2 gene notably improved the vector’s expression efficiency in leafhopper cells. Using the optimized vector, we have for the first time traced the cellular localization of the proteins encoded by rice yellow stunt virus (RYSV) in cells of its insect vector and demonstrated that P6 protein is a component of the viroplasm.

A novel pedestrian detection system based on vision in urban traffic situations is presented to help the driver perceive the pedestrian ahead of the vehicle. To enhance the accuracy and to decrease the time spent on pedestrian detection in such complicated situations, the pedestrian is detected by dividing their body into several parts according to their corresponding features in the image. The candidate pedestrian leg is segmented based on the gentle AdaBoost algorithm by training the optimized histogram of gradient features. The candidate pedestrian head is located by matching the pedestrian head and shoulder model above the region of the candidate leg. Then the candidate leg, head and shoulder are combined by parts constraint and threshold adjustment to verify the existence of the pedestrian. Finally, the experiments in real urban traffic circumstances were conducted. The results show that the proposed pedestrian detection method can achieve pedestrian detection rate of 92.1% with the average detection time of 0.2257 s.

Background Glycine air polishing has been proved to be safe, comfortable and time-saving. Whether it could substitute ultrasonic scaling to remove dental plaque biofilm during periodontal maintenance remains unclear. The purposes of this study were to evaluate the effect of supragingival glycine air polishing (SGAP) on the subgingival periodontal pathogens during maintenance therapy and to check the association of periodontal pathogens and clinical parameters. Methods Twenty-three chronic periodontitis patients during their maintenance therapy were enrolled in the 12-week study. According to randomized split-mouth design, the test side was treated with SGAP (65 μm), while the control side was treated with supragingival ultrasonic scaling and polishing (SUSP) with rubber cup. Clinical examination including plaque index (PLI), probing depth (PD), bleeding index (BI) were performed at baseline and 12 weeks post-treatment. Sampling of the subgingival plaque at each investigational site (mesiobuccal site of the mandibular first molar) was performed at baseline and 2, 4, 8, 12 weeks after maintenance treatment. Four periodontal pathogens including Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola and Fusobacterium nucleatum were detected by 16S rDNA polymerase chain reaction. Results Clinical status generally improved after treatment in both groups. PLI in both groups, PD in SGAP group and bleeding on probing (%) in SUSP group significantly decreased after treatment (p < 0.05). There was no significant difference of clinical parameters between two groups before and after treatment. The detection rates of P. gingivalis, T. denticola in both groups, T. forsythia in SUSP group and F. nucleatum in SGAP group decreased after maintenance treatment in both groups, although no significant difference was found, and it rebound to baseline level at 12 weeks after maintenance treatment. There was no significant difference between SGAP group and SUSP group at any time point. T. denticola-positive sites had significantly greater BI than T. denticola-negative sites (p < 0.05). Discussion Supragingival glycine air polishing had a reliable effect in removing subgingival dental plaque biofilm during maintenance period, and three months may be a proper maintenance interval for pockets not more than 5 mm.

Pedestrian detection and tracking is the key to autonomous vehicle navigation systems avoiding potentially dangerous situations. Firstly, the probability distribution of colour information is established after a pedestrian is located in an image. Then the detected results are utilized to initialize a Kalman filter to predict the possible position of the pedestrian centroid in the future frame. A Camshift tracking algorithm is used to track the pedestrian in the specific search window of the next frame based on the prediction results. The actual position of the pedestrian centroid is output from the Camshift tracking algorithm to update the gain and error covariance matrix of the Kalman filter. Experimental results in real traffic situations show the proposed pedestrian tracking algorithm can achieve good performance even when they are partly occluded in inconsistent illumination circumstances.

Currently, a mechanical arm or manipulator needs to be programmed by humans in advance to define its motion trajectory before practical use. However, the programming is tedious and high-cost, which renders such manipulators unable to perform various different tasks easily and quickly. This article focuses on the design of a vision-guided manipulator without explicit human programming. The proposed demonstration-driven system mainly consists of a manipulator, control box, and camera. Instead of programming of the detailed motion trajectory, one only needs to show the system how to perform a given task manually. Based on internal object recognition and motion detection algorithms, the camera can capture the information of the task to be performed and generate the motion trajectories for the manipulator to make it copy the human demonstration. The movement of the joints of the manipulator is given by a trajectory planner in the control box. Experimental results show that the system can imitate humans easily, quickly, and accurately for common tasks such as sorting and assembling objects. Teaching the manipulator how to complete the desired motion can help eliminate the complexity of programming for motion control.

In order to detect the obstacle from the large amount of 3D LIDAR data in hybrid cross-country environment for unmanned ground vehicle, a new graph approach based on Markov random field was presented. Firstly, the preprocessing method based on the maximum blurred line is applied to segment the projection of every laser scan line in x-y plane. Then, based on K-means clustering algorithm, the same properties of the line are combined. Secondly, line segment nodes are precisely positioned by using corner detection method, and the next step is to take advantage of line segment nodes to build an undirected graph for Markov random field. Lastly, the energy function is calculated by means of analyzing line segment features and solved by graph cut. Two types of line mark are finally classified into two categories: ground and obstacle. Experiments prove the feasibility of the approach and show that it has better performance and runs in real time.