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Abstract A bridge disease identification approach based on an enhanced YOLO v3 algorithm is suggested to increase the accuracy of apparent disease detection of concrete bridges under complex backgrounds. First, the YOLO v3 network structure is enhanced to better accommodate the dense distribution and large variation of disease scale characteristics, and the detection layer incorporates the squeeze and excitation (SE) networks attention mechanism module and spatial pyramid pooling module to strengthen the semantic feature extraction ability. Secondly, CIoU with better localization ability is selected as the loss function for training. Finally, the K-means algorithm is used for anchor frame clustering on the bridge surface disease defects dataset. 1363 datasets containing exposed reinforcement, spalling, and water erosion damage of bridges are produced, and network training is done after manual labelling and data improvement in order to test the efficacy of the algorithm described in this paper. According to the trial results, the YOLO v3 model has enhanced more than the original model in terms of precision rate, recall rate, Average Precision (AP), and other indicators. Its overall mean Average Precision (mAP) value has also grown by 5.5%. With the RTX2080Ti graphics card, the detection frame rate increases to 84 Frames Per Second, enabling more precise and real-time bridge illness detection.

In this study, dual-root soybean (Glycine max L. Merr.) plants, with one side nodulated and the other nonnodulated, were used as experimental materials. The nonnodulated lateral roots were treated with excessive nitrate (200 mg·L−1 nitrogen) for three days, followed by a three-day nitrate withdrawal, and then subjected to excessive nitrate again for another three days. Meanwhile, the nodulated side was continuously supplied with nitrogen-free nutrient solution. We measured the nitrogenase activity, nodule quantity, and concentrations of sucrose, starch, and soluble sugars, along with the microstructure of the nodules. By analyzing these data, we aim to provide theoretical insights into how indirect nitrate supply affects the nitrogen fixation capacity of nodules. The results demonstrated that indirect supply of nitrate to the soybean nodules reduced the nodule nitrogen fixation ability, which was manifested in the decrease in nodule dry weight, nodule number, and nitrogenase activity. The reason was found to be related to the decrease in carbon sources (sucrose, starch, and soluble sugar) allocated to the nodules. Further observation of the internal structure of the nodules found that the number of infected cells in the nodules decreased with the addition of nitrate, and increased with its withdrawal. However, the addition and withdrawal of nitrate did not change the effect of nitrate on the structure of infected cells around the nodules after the first addition of nitrate. These may be one of the important reasons why nitrate indirectly affects the activity of nitrogenase in nodules.

The rice production system in China is facing challenges, including declining soil fertility and a stagnant rice yield. This study aimed to test whether integrating the return of straw to fields with less power puddling could simultaneously enhance soil fertility and rice yields. Therefore, field experiments were conducted in Heilongjiang Province, a key rice-growing region in China, from 2017 to 2021, using three different planting methods: control group (CK), straw return (SR) and straw return integrated with less power puddling (SR + LP). The results showed that small soil aggregates (particle diameter < 0.25 mm) and soil bulk density were significantly decreased when straw return was integrated with less power puddling. These changes contributed to the preservation of soil structure. Simultaneously, this approach significantly increased soil ammonium nitrogen content from 9.9 to 10.9 mg kg−1, organic matter content from 35.0 to 36.2 g kg−1, available nitrogen content from 140.5 to 147.0 mg kg−1 and available potassium content from 128.6 to 136.8 mg kg−1 at mature stage on average. Consequently, the post-heading stored assimilates accumulation of rice was increased from 6.12 to 6.43 t ha−1, and the nitrogen, phosphorus and potassium accumulation of rice were increased by 7.85 kg ha−1, 1.13 kg ha−1 and 5.68 kg ha−1, respectively. These changes ultimately resulted in a higher 1000 g weight and filled grain rate, providing the foundation for higher yields (an increase from 9.31 t ha−1 to 9.55 t ha−1). Furthermore, this approach also increased the net income for farmers by USD 14 t ha−1. In summary, this study demonstrates that integrating straw return with less power puddling can enhance soil’s nutrient supply and retention capacity. This enhancement may boost the absorption and transportation of nutrients, ultimately establishing the groundwork for higher yields and economic benefits by enhancing the 1000 g weight and filled grain rate. Future research should delve deeper into its applicability across different ecosystems and investigate the yield-increasing mechanisms.

BackgroundThe nitrate regulates soybean nodulation and nitrogen fixation systemically, mainly in inhibiting nodule growth and reducing nodule nitrogenase activity, but the reason for its inhibition is still inconclusive.MethodsThe systemic effect of nitrate on nodule structure, function, and carbon distribution in soybean (Glycine max (L.) Merr.) was studied in a dual-root growth system, with both sides inoculated with rhizobia and only one side subjected to nitrate treatment for four days. The non-nodulating side was genetically devoid of the ability to form nodules. Nutrient solutions with nitrogen concentrations of 0, 100, and 200 mg L-1 were applied as KNO3 to the non-nodulating side, while the nodulating side received a nitrogen-free nutrient solution. Carbon partitioning in roots and nodules was monitored using 13C-labelled CO2. Other nodule responses were measured via the estimation of the nitrogenase activity and the microscopic observation of nodule ultrastructure.ResultsElevated concentrations of nitrate applied on the non-nodulating side caused a decrease in the number of bacteroids, fusion of symbiosomes, enlargement of the peribacteroid spaces, and onset of degradation of poly-β-hydroxybutyrate granules, which is a form of carbon storage in bacteroids. These microscopic observations were associated with a strong decrease in the nitrogenase activity of nodules. Furthermore, our data demonstrate that the assimilated carbon is more likely to be allocated to the non-nodulating roots, as follows from the competition for carbon between the symbiotic and non-symbiotic sides of the dual-root system.ConclusionWe propose that there is no carbon competition between roots and nodules when they are indirectly supplied with nitrate, and that the reduction of carbon fluxes to nodules and roots on the nodulating side is the mechanism by which the plant systemically suppresses nodulation under nitrogen-replete conditions.

Quantifying the level of CO2, the main greenhouse gas (GHG), is essential for research on regional and global climate change, especially in the densely populated North China Plain with its severe CO2 emissions. In this study, 12 airborne flights were managed and conducted during the autumn–winter period of 2018–2019 in downtown Shijiazhuang and its surrounding areas, which are representative of the typical urban conditions in the North China Plain, to explore the spatial and temporal distributions of CO2. The results showed that the measured columnar averages of CO2 ranged between 399.9 ± 1.5 and 443.8 ± 31.8 ppm; the average of the 12 flights was 412.1 ppm, slightly higher than the globally averaged 410.5 ± 0.20 ppm and the 2 background concentrations of 411.6 ± 2.1 ppm and 411.4 ± 0.2 ppm in low-latitude Mauna Loa and middle-latitude Waliguan in 2019, indicating the potential influences of anthropogenic activities. The typical stratification of the planetary boundary layer (PBLH), residual layer (RL), and elevated inversion layer (IL) was crucial in constraining the high CO2 concentrations. This illustrated that the warming effect of CO2 within the PBLH may also have some influences on regulating the thermal structure of the low troposphere. Based on a backward trajectory analysis, it was evidenced that there were three different categories of air masses for autumn and one category for winter. Both trajectories in the PBL, i.e., below 1000 m, from the local and southern areas with tremendous anthropogenic emissions (autumn) and from the western regions (winter) led to comparatively high levels of CO2, but the mid-tropospheric CO2 concentrations above 1000 m were commonly homogeneously distributed, with higher levels appearing in winter because the concentration in the free troposphere followed the global seasonal pattern, with a summer minimum and winter maximum as a result of the seasonality of the net CO2 exchange and the balance between photosynthesis and respiration. These results provide an in-depth understanding of the vertical concentrations of tropospheric CO2 in the North China Plain, which will offer scientific references for the evaluation of carbon accounting and carbon emissions.

In response to the lack of relevant research on the health monitoring system and assessment of the structural safety status of a cable-stayed bridge across the sea, the real-time monitoring data was determined by the health monitoring system installed on the bridge structure. Strain and displacement data for the bridge structure were analyzed and processed. Based on operational research principles, a safety condition assessment of the Channel 1 Bridge was conducted using the Analytic Hierarchy Process (AHP). First, the reserve strength method is applied to determine the weight proportion of monitoring indicators such as strain and displacement. Secondly, the weight proportion of each monitoring indicator at different cross-sectional positions is determined. Then, the hierarchical division of the cable-stayed bridge structure is performed from the lowest layer, and the rating level of the Channel 1 Bridge structure is obtained using the variable weight synthesis method. This provides a basis for management decisions in the bridge maintenance department and serves as an example for future safety assessments of medium-span cable-stayed bridges over the sea.

Arbuscular mycorrhizal fungi (AMF) are known to improve plant stress tolerance by regulating proline accumulation, and nitric oxide (NO) plays an important signaling role in proline metabolism. Environmental nitrogen (N) affects AMF colonization and its contribution to host plants resistance to stress conditions. However, the relationship between proline metabolism and NO in mycorrhizal rice and the effect of N application on symbiont proline metabolism under low temperature have not been established. Pot culture experiments with different temperature, N and exogenous NO donor treatments were conducted with non-mycorrhizal and mycorrhizal rice. The results showed that AMF enhanced rice proline accumulation under low-temperature stress and decreased glutamate (Glu) and ornithine (Orn) concentrations significantly. In comparison with non-mycorrhizal rice, AMF colonization significantly decreased the Glu concentration, but had little effect on the Orn concentration under low-temperature stress, accompanied by increasing expression of OsP5CS2, OsOAT and OsProDH1. Exogenous application of NO increased proline concentration both under normal and low temperature, which exhibited a higher increase in mycorrhizal rice. NO also triggered the expression of key genes in the Glu and Orn pathways of proline synthesis as well as proline degradation. Higher N application decreased the AMF colonization, and AMF showed greater promotion of proline metabolism at low N levels under low temperature stress by regulating the Glu synthetic pathway. Meanwhile, AMF increased rice nitrate reductase (NR) and nitric oxide synthase (NOS) activities and then enhanced NO accumulation under low N levels. Consequently, it could be hypothesized that one of the mechanisms by which AMF improves plant resistance to low-temperature stress is the accumulation of proline via enhancement of the Glu and Orn synthetic pathways, with the involvement of the signaling molecule NO. However, the contribution of AMF to rice proline accumulation under low-temperature stress was attenuated by high N application.

Although Fraxinellone (Frax) isolated from Dictamnus albus L. possessed excellent anti-hepatic fibrosis activity, oral administration of Frax suffered from the inefficient therapeutic outcome in vivo due to negligible oral absorption. At present, the oral formulation of Frax is rarely exploited. For rational formulation design, we evaluated preabsorption risks of Frax and found that Frax was rather stable while poorly dissolved in the gastrointestinal tract (78.88 μg/mL), which predominantly limited its oral absorption. Further solubility test revealed the outstanding capacity of cyclodextrin derivatives (CDs) to solubilize Frax (6.8–12.8 mg/mL). This led us to study the inclusion complexes of Frax with a series of CDs and holistically explore their drug delivery performance. Characterization techniques involving 1H-NMR, FT-IR, DSC, PXRD, and molecular docking confirmed the most stable binding interactions when Frax complexed with 6-O-α-D-maltosyl-β-cyclodextrin (G2-β-CD-Frax). Notably, G2-β-CD-Frax exhibited the highest solubilizing capacity, fast dissolution rate, and superior Caco-2 cell internalization with no obvious toxicity. Pharmacokinetic studies demonstrated markedly higher oral bioavailability of G2-β-CD-Frax (5.8-fold that of free drug) than other Frax-CDs. Further, long-term administration of G2-β-CD-Frax (5 mg/kg) efficiently inhibited CCl4-induced hepatic fibrosis in the mouse without inducing any toxicity. Our results will inspire the continued advancement of optimal oral Frax formulations for anti-fibrotic therapy.

Abstract Zinc (Zn) can improve resistance of rice plants to abiotic stress and promote the recovery of rice tillers by influencing auxin (IAA) synthesis, Zn absorption is closely related to nitrogen (N) concentrations; however, the mechanisms by which Zn regulates rice tiller recovery at low temperatures under different N levels are rarely studied. In this study, a solution culture experiment was conducted at two temperatures, three different Zn concentrations, and two N concentrations. Low temperature during the vegetative stage damaged the rice antioxidant system, suppressed nutrient uptake, and decreased the number of tillers. Increasing Zn application improved the resistance of rice plants to low‐temperature stress under normal N levels, enhanced nutrient absorption, improved tiller bud cytokinin (CTK) concentrations, and the CTK/IAA ratio, which accelerated tiller recovery relative to plants receiving standard Zn treatment. Shoot Zn concentrations were positively correlated with tiller numbers at normal N levels. High N attenuated the positive effect of Zn on rice tillering at low temperatures due to higher shoot Zn and IAA accumulation, and lower tiller buds CTK/IAA ratios. However, appropriate Zn application under high N levels was conducive to breaking tiller dormancy and promoting tillering growth spurts when recovering to normal temperature, which was related to the synergistic regulation of hormone balance and nutrient absorption by N and Zn. In conclusion, Zn could enhance rice low‐temperature stress resilience and facilitate tiller recovery via balancing the hormones in tiller buds. However, higher environmental N limited the stimulation of Zn on rice tillering under low temperature.

Magnesium (Mg) plays a crucial role in rice yield. Heilongjiang Province is the main rice-producing region of China, playing an important role in guaranteeing China's and the world's grain security. However, rarely Mg fertilization is applied in this province. Soil Mg status of main rice-producing areas in Heilongjiang Province was investigated and Mg fertilizer experiments were conducted aiming to provide fertilizer recommendation in this region. A total of 358 soil samples from the 0–20 cm and 20–40 cm soil layer from the main rice-producing areas of Heilongjiang Province were collected to analyze soil exchangeable Mg (ex-Mg) and relative chemical properties. Meanwhile, field experiments of soil and foliar Mg application were performed in 2017–2019 to identify the effect of this nutrient on rice yield. The results showed that the ex-Mg concentration in the 0–20 cm and 20–40 cm soil layer was 282 mg kg−1 and 243 mg kg−1, respectively. Moreover, ex-Mg ranged on the abundant and exceptionally abundant level accounted for 75% in 0–20 cm and 55.3% in 20–40 cm. The ex-Mg concentration in the upper soil layer was higher than in the lower soil layer and varied depending on regions, which the west part of Heilongjiang Province showed the highest concentration in both soil layers. Correlation analysis showed that there had a significant (P < 0.05) linear relationship between ex-Mg and pH, CEC, ex-K, Ca, K/Mg, and Ca/Mg. Meanwhile, the results of path coefficients demonstrated that pH, CEC, and Ca/Mg had the most direct effect on ex-Mg concentration among these above factors. Soil Mg application had little effect on rice yield, which might be related to the soil Mg concentration and availability, and root uptake activity. Foliar Mg application increased rice yield by 8.45% (P < 0.05) compared to without Mg treatment, increased 1,000-grain weight by 2.62% (P < 0.05), and spikelet number per panicle by 4.19% (P < 0.05). In general, the paddy soil ex-Mg concentration in Heilongjiang Province was abundant. Soil-applied Mg played little role in rice yield in ex-Mg abundant regions, while foliar application increased rice yields significantly via increasing 1,000-grain weight and spikelet number per panicle.

Previous studies of speech emotion recognition using either empirical features (e.g., F0, energy, and voice probability) or spectrogram-based statistical features. The empirical features can highlight the human knowledge of emotion recognition, while the statistical features enable a general representation, but they do not emphasize human knowledge sufficiently. However, the use of these two kinds of features together can complement some features that may be unconsciously used by humans in daily life but have not been realized yet. Based on this consideration, this paper proposes a dynamic fusion framework to utilize the potential advantages of the complementary spectrogram-based statistical features and the auditory-based empirical features. In addition, a kernel extreme learning machine (KELM) is adopted as the classifier to distinguish emotions. To validate the proposed framework, we conduct experiments on two public emotional databases, including Emo-DB and IEMOCAP databases. The experimental results demonstrate that the proposed fusion framework significantly outperforms the existing state-of-the-art methods. The results also show that the proposed method, by integrating the auditory-based features with spectrogram-based features, could achieve a notably improved performance over the conventional methods.

In order to make a robot track a desired trajectory with high precision and steady gait, a novel intelligent controller was designed based on a new mechanical structure and optimized foot trajectory. Kinematics models in terms of the D-H method were established to analyze the relationship between the angle of the driving joint and the foot position. Inspired by a dog’s diagonal trot on a flat terrain, foot trajectory planning in the swing and support phases without impact were fulfilled based on the compound cycloid improved by the Bézier curve. Both the optimized cascade proportional–integral–derivative (PID) control system and improved fuzzy adaptive PID control system were applied to realize the stable operation of a quadruped robot, and their parameters were optimized by the sparrow search algorithm. The convergence speed and accuracy of the sparrow search algorithm were verified by comparing with the moth flame optimization algorithm and particle swarm optimization algorithm. Finally, a co-simulation with MATLAB and ADAMS was utilized to compare the effects of the two control systems. The results of both displacement and velocity exhibit that the movement of a quadruped bionic robot with fuzzy adaptive PID control systems optimized by the sparrow search algorithm possessed better accuracy and stability than cascade PID control systems. The motion process of the quadruped robot in the co-simulation process also demonstrates the effectiveness of the designed mechanical structure and control system.

Motion segmentation plays a central role in a variety of computer vision and pattern recognition applications. In moving camera videos, the dynamic background caused by camera motion and the object motions caused by multiple moving objects are mixed and dependent with each other making the segmentation of camera motion and object motions quite difficult. This is the known dependent motion segmentation. Although motion segmentation in static scenes is a relative easy work, the dependent motion segmentation in dynamic scenes is very challenging due to the high mixture and dependence between camera motion and object motions. Recently, a large number of works have been developed for the task of dependent motion segmentation. However, their performances are still far behind human perceptions. In this paper, we studied, analyzed, and reviewed the most important and recent developed dependent motion segmentation techniques and proposed a classification strategy to categorize these techniques into different groups according to their characteristics and features. Furthermore, we also discussed the advantages and disadvantages of each kind of techniques and provided suggestions for further research directions.

Mitogen-activated protein kinase (MAPK) cascades play important roles in the stress response in both plants and microorganisms. The mycorrhizal symbiosis established between arbuscular mycorrhizal fungi (AMF) and plants can enhance plant drought tolerance, which might be closely related to the fungal MAPK response and the molecular dialogue between fungal and soybean MAPK cascades. To verify the above hypothesis, germinal Glomus intraradices (syn. Rhizophagus irregularis) spores and potted experiments were conducted. The results showed that AMF GiMAPKs with high homology with MAPKs from Saccharomyces cerevisiae had different gene expression patterns under different conditions (nitrogen starvation, abscisic acid treatment, and drought). Drought stress upregulated the levels of fungi and soybean MAPK transcripts in mycorrhizal soybean roots, indicating the possibility of a molecular dialogue between the two symbiotic sides of symbiosis and suggesting that they might cooperate to regulate the mycorrhizal soybean drought-stress response. Meanwhile, the changes in hydrogen peroxide, soluble sugar, and proline levels in mycorrhizal soybean as well as in the accelerated exchange of carbon and nitrogen in the symbionts were contributable to drought adaptation of the host plants. Thus, it can be preliminarily inferred that the interactions of MAPK signals on both sides, symbiotic fungus and plant, might regulate the response of symbiosis and, thus, improve the resistance of mycorrhizal soybean to drought stress.

The transverse carpal ligament (TCL) forms the volar boundary of the carpal tunnel and may provide mechanical constraint to the median nerve, leading to carpal tunnel syndrome. Therefore, the mechanical properties of the TCL are essential to better understand the etiology of carpal tunnel syndrome. The purpose of this study was to investigate the in vivo TCL stiffness using acoustic radiation force impulse (ARFI) imaging. The shear wave velocity (SWV) of the TCL was measured using Virtual Touch IQ(TM) software in 15 healthy, male subjects. The skin and the thenar muscles were also examined as reference tissues. In addition, the effects of measurement location and ultrasound transducer compression on the SWV were studied. The SWV of the TCL was dependent on the tissue location, with greater SWV values within the muscle-attached region than those outside of the muscle-attached region. The SWV of the TCL was significantly smaller without compression (5.21 ± 1.08 m/s) than with compression (6.62 ± 1.18 m/s). The SWV measurements of the skin and the thenar muscles were also affected by transducer compression, but to different extents than the SWV of the TCL. Therefore to standardize the ARFI imaging procedure, it is recommended that a layer of ultrasound gel be maintained to minimize the effects of tissue compression. This study demonstrated the feasibility of ARFI imaging for assessing the stiffness characteristics of the TCL in vivo, which has the potential to identify pathomechanical changes of the tissue.

PurposesPreimplant diagnostic magnetic resonance imaging is the gold standard for image-guided tandem-and-ovoids (T&O) brachytherapy for cervical cancer. However, high dose rate brachytherapy planning is typically done on postimplant CT-based high-risk clinical target volume (HR-CTVCT ) because the transfer of preimplant Magnetic resonance (MR)-based HR-CTV (HR-CTVMR ) to the postimplant planning CT is difficult due to anatomical changes caused by applicator insertion, vaginal packing, and the filling status of the bladder and rectum. This study aims to train a dual-path convolutional neural network (CNN) for automatic segmentation of HR-CTVCT on postimplant planning CT with guidance from preimplant diagnostic MR.MethodsPreimplant T2-weighted MR and postimplant CT images for 65 (48 for training, eight for validation, and nine for testing) patients were retrospectively solicited from our institutional database. MR was aligned to the corresponding CT using rigid registration. HR-CTVCT and HR-CTVMR were manually contoured on CT and MR by an experienced radiation oncologist. All images were then resampled to a spatial resolution of 0.5 × 0.5 × 1.25 mm. A dual-path 3D asymmetric CNN architecture with two encoding paths was built to extract CT and MR image features. The MR was masked by HR-CTVMR contour while the entire CT volume was included. The network put an asymmetric weighting of 18:6 for CT: MR. Voxel-based dice similarity coefficient (DSCV ), sensitivity, precision, and 95% Hausdorff distance (95-HD) were used to evaluate model performance. Cross-validation was performed to assess model stability. The study cohort was divided into a small tumor group (40 cc) based on the HR-CTVCT for model evaluation. Single-path CNN models were trained with the same parameters as those in dual-path models.ResultsFor this patient cohort, the dual-path CNN model improved each of our objective findings, including DSCV , sensitivity, and precision, with an average improvement of 8%, 7%, and 12%, respectively. The 95-HD was improved by an average of 1.65 mm compared to the single-path model with only CT images as input. In addition, the area under the curve for different networks was 0.86 (dual-path with CT and MR) and 0.80 (single-path with CT), respectively. The dual-path CNN model with asymmetric weighting achieved the best performance with DSCV of 0.65 ± 0.03 (0.61-0.70), 0.79 ± 0.02 (0.74-0.85), and 0.75 ± 0.04 (0.68-0.79) for small, medium, and large group. 95-HD were 7.34 (5.35-10.45) mm, 5.48 (3.21-8.43) mm, and 6.21 (5.34-9.32) mm for the three size groups, respectively.ConclusionsAn asymmetric CNN model with two encoding paths from preimplant MR (masked by HR-CTVMR ) and postimplant CT images was successfully developed for automatic segmentation of HR-CTVCT for T&O brachytherapy patients.