Variations with respect to perspective, lighting, weather, and interference from dynamic objects may all have an impact on the accuracy of the entire system during autonomous positioning and during ...the navigation of mobile visual simultaneous localization and mapping (SLAM) robots. As it is an essential element of visual SLAM systems, loop closure detection plays a vital role in eradicating front-end-induced accumulated errors and guaranteeing the map’s general consistency. Presently, deep-learning-based loop closure detection techniques place more emphasis on enhancing the robustness of image descriptors while neglecting similarity calculations or the connections within the internal regions of the image. In response to this issue, this article proposes a loop closure detection method based on similarity differences between image blocks. Firstly, image descriptors are extracted using a lightweight convolutional neural network (CNN) model with effective loop closure detection. Subsequently, the image pairs with the greatest degree of similarity are evenly divided into blocks, and the level of similarity among the blocks is used to recalculate the degree of the overall similarity of the image pairs. The block similarity calculation module can effectively reduce the similarity of incorrect loop closure image pairs, which makes it easier to identify the correct loopback. Finally, the approach proposed in this article is compared with loop closure detection methods based on four distinct CNN models with a recall rate of 100% accuracy; said approach performs significantly superiorly. The application of the block similarity calculation module proposed in this article to the aforementioned four CNN models can increase the recall rate’s accuracy to 100%; this proves that the proposed method can successfully improve the loop closure detection effect, and the similarity calculation module in the algorithm has a certain degree of universality.
Hu (
), referred to as "Fu-Pen-Zi" in Chinese, has great medicinal and dietary values since ancient times. The dried fruits of
have been widely used in traditional Chinese medicine (TCM) for the ...treatment of kidney enuresis and urinary frequency for centuries. According to current findings,
has been reported to contain a variety of chemical constituents, mostly triterpenoids, diterpenoids, flavonoids, and organic acids. These compounds have been demonstrated to be the major bioactive components responsible for pharmacological effects such as anticomplementary, anticancer, antioxidant, antimicrobial, and anti-inflammatory functions. Therefore, this review focused on the up-to-date published data of the literature about
and comprehensively summarized its phytochemistry, pharmacology, quality control, and toxicity to provide a beneficial support to its further investigations and applications in medicines and foods.
Combining inertial navigation system (INS) and ultra-wideband (UWB) technologies can effectively compensate for their respective shortcomings, thus significantly enhancing the accuracy of indoor ...positioning systems. However, in the process of fusing these two technologies, signal fading under non-line-of-sight (NLOS) conditions, multipath effects, and errors accumulated by the INS over a long period of time are still key issues that need to be addressed. To cope with these challenges, a new fusion localization algorithm is proposed in this study. The algorithm employs a combination of fuzzy C-mean (FCM) and K-Medoids algorithms for UWB for position computation on the one hand, and an Implicit Unscented Particle Filter (IUPF)-enhanced INS for navigation information processing on the other. In addition, based on the INS error equation, this algorithm realizes the effective fusion of UWB and INS positioning information through the Minimum Error Entropy Extended Kalman Filter (MEE-EKF) technique. This integrated approach significantly improves the accuracy and stability when dealing with the localization problem in complex indoor environments. After simulation experiments under different noise conditions and real environment experiments, the algorithm proposed in this study shows significant advantages in terms of localization performance over the traditional UWB/INS localization methods in recent years. In real experiments, the algorithm achieves an average of 36.15% improvement in positioning accuracy.
The impact of lipotoxicity on the development of lung fibrosis is unclear. Saturated fatty acids, such as palmitic acid (PA), activate endoplasmic reticulum (ER) stress, a cellular stress response ...associated with the development of idiopathic pulmonary fibrosis (IPF). We tested the hypothesis that PA increases susceptibility to lung epithelial cell death and experimental fibrosis by modulating ER stress. Total liquid chromatography and mass spectrometry were used to measure fatty acid content in IPF lungs. Wild-type mice were fed a high-fat diet (HFD) rich in PA or a standard diet and subjected to bleomycin-induced lung injury. Lung fibrosis was determined by hydroxyproline content. Mouse lung epithelial cells were treated with PA. ER stress and cell death were assessed by Western blotting, TUNEL staining, and cell viability assays. IPF lungs had a higher level of PA compared with controls. Bleomycin-exposed mice fed an HFD had significantly increased pulmonary fibrosis associated with increased cell death and ER stress compared with those fed a standard diet. PA increased apoptosis and activation of the unfolded protein response in lung epithelial cells. This was attenuated by genetic deletion and chemical inhibition of CD36, a fatty acid transporter. In conclusion, consumption of an HFD rich in saturated fat increases susceptibility to lung fibrosis and ER stress, and PA mediates lung epithelial cell death and ER stress via CD36. These findings demonstrate that lipotoxicity may have a significant impact on the development of lung injury and fibrosis by enhancing pro-death ER stress pathways.
Early identification of gastrointestinal (GI) bleeding in children with abdominal Henoch-Schönlein purpura (HSP) is essential for their subsequent treatment, and a risk prediction model for GI ...bleeding in abdominal HSP was constructed in this study to assist physicians in their decision-making. In a single-center retrospective study, the children collected were divided into two parts, a training set and a validation set, according to the time of admission. In the training set, univariate analysis was performed to compare demographic data and laboratory tests between the two groups of children with GI and non-GI bleeding, and the independent risk factors were derived using binary logistic equations to develop a scoring model for predicting GI bleeding in children by odds ratio (OR) values and receiver operating characteristic curves. The scoring model was then internally validated in validation set. The results showed that there were 11 indicators were statistically different between the two groups in the training set, including white blood cells, neutrophil-to-lymphocyte ratio, platelets, eosinophils (EO), high sensitivity C-reactive protein (hsCRP), activated partial thromboplastin time (APTT), sodium, potassium (K), albumin (ALB), Total bilirubin, and Immunoglobulin E (IgE) in the univariate analysis. Among them, the independent risk factors for GI bleeding included the six indicators of EO ≤ 0.045×10^9/L, hsCRP ≥ 14.5 mg/L, APTT ≤ 28.1 s, K ≥ 4.18 mmol/L, ALB ≤ 40.6 g/L, and IgE ≥ 136 ng/mL. According to the OR values, where EO ≤ 0.045 ×10^9/L, hsCRP ≥ 14.5 mg/L, APTT ≤ 28.1 s, ALB ≤ 40.6 g/L each scored 3 points, K ≥ 4.18 mmol/L, IgE ≥ 136 ng/mL each scored 2 points, and the total score was 0-16 points. The sensitivity and specificity of predicting GI bleeding were 88.7% and 64.2%, respectively, when the child scored ≥ 7 points. In the validation set, the sensitivity, specificity and accuracy of the model in predicting GI bleeding were 77.4%, 74.5% and 75.2%, respectively. In conclusion, the construction of a scoring model to predict the risk of GI bleeding from abdominal HSP would greatly assist pediatricians in predicting and identifying children at high risk for GI bleeding at an early stage.
As an extension of conventional gradient, anti-symmetric oblique coupling gradient has a superior modal modification ability on composite laminates embedded with pre-strained shape memory alloys ...(SMA) wires, which is beneficial to suppress modal resonance of composite laminates in the thermal environment. This paper presents an anti-symmetric oblique coupling gradient model of SMA along the thickness direction. That is, the gradient model of SMA wires’ orientation and the positive and negative gradient model of SMA volume fraction. Considering the internal force of composite laminates composed of the pre-strain recovery force of SMA and the thermal expansion force of the substrate, the free vibration equation of composite laminates with additional internal forces energy is derived from first-order shear plate theory and Hamilton principle. The influence of coupling gradient parameters on the thermal modal performance of SMA composite laminates is analyzed and verified by experiments. The proposed anti-symmetric oblique coupling gradient SMA wires’ distribution form effectively exerts the recovery stress generated by SMA tensile pre-strain, i.e., effectively improves the stiffness and critical buckling temperature. Coupling gradient distribution broadens the frequency modulation range, which makes the fine regulation of the natural frequency and critical buckling temperature feasible.
Clinopodium gracile (Benth.) Matsum (C. gracile) is an annual herb with pharmacological properties effective in the treatment of various diseases, including hepatic carcinoma. Triterpenoid saponins ...are crucial bioactive compounds in C. gracile. However, the molecular understanding of the triterpenoid saponin biosynthesis pathway remains unclear.
In this study, we performed RNA sequencing (RNA-Seq) analysis of the flowers, leaves, roots, and stems of C. gracile plants using the BGISEQ-500 platform. The assembly of transcripts from all four types of tissues generated 128,856 unigenes, of which 99,020 were mapped to several public databases for functional annotation. Differentially expressed genes (DEGs) were identified via the comparison of gene expression levels between leaves and other tissues (flowers, roots, and stems). Multiple genes encoding pivotal enzymes, such as squalene synthase (SS), or transcription factors (TFs) related to triterpenoid saponin biosynthesis were identified and further analyzed. The expression levels of unigenes encoding important enzymes were verified by quantitative real-time PCR (qRT-PCR). Different chemical constituents of triterpenoid saponins were identified by Ultra-Performance Liquid Chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS).
Our results greatly extend the public transcriptome dataset of C. gracile and provide valuable information for the identification of candidate genes involved in the biosynthesis of triterpenoid saponins and other important secondary metabolites.
•It reviews studies using street view imagery to assess SDGs.•Street view imagery could help assess SDGs 3, 11, 2, and 13.•Element and perception features are often extracted from street view ...imagery.•The greenery view index has been related to many SDGs.•Actions addressing features of street view imagery could help SDGs.
With limited time to achieve the 2030 Agenda for Sustainable Development, the world needs effective, scalable approaches to measure and monitor global progress toward the 17 Sustainable Development Goals (SDGs). Given that many SDGs are closely related to the environment in which people live, satellite data are commonly used for SDG assessment, but they are only based on a top-down view and have inherent technical issues (e.g., insufficient spatial resolution and cloud coverage). In recent years, street view imagery (SVI), as an emerging source of remote sensing data, has been an indispensable supplement to monitor SDGs, by recording the environment from an eye-level view. However, the systematic and comprehensive understanding of SVI applications to promote SDGs is insufficient. We reviewed SVI-related studies of SDGs and found that SVI is mainly used for good health and well-being (SDG 3), sustainable cities and communities (SDG 11), zero hunger (SDG 2), and climate action (SDG 13). The SVI-based greenery view index was the most common element feature related to SDGs. The SVI-derived human perception features were also often used to assess SDG 3 and SDG 11. Future studies may further investigate the potential mechanisms between SVI-based features and SDGs. This review provides a comprehensive summary and guidance for governments and scholars worldwide to assess SDGs based on SVI in the future.
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