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Accurate and high-throughput maize plant phenotyping is vital for crop breeding and cultivation research. Tassel-related phenotypic parameters are important agronomic traits. However, fully automatic and fine tassel organ segmentation of maize shoots from three-dimensional (3D) point clouds is still challenging. To address this issue, a tassel point cloud segmentation method based on point cloud super voxels clustering and local geometric features was proposed in this study. Firstly, the undirected graph of the maize plant point cloud was established, the edge weights were calculated by using the difference of normal vectors, and the spectral clustering method was used to cluster the point cloud to form multiple super voxel sub-regions. Then, the principal component analysis method was used to find the two end regions of the plant and based on the observation of the straight direction of the bottom stem regions, the top and bottom regions were distinguished by the point cloud linear features. Finally, the tassel points were identified based on the plane local features of the point cloud. The sub-regions of the top region of the plant were classified into leaf regions, tassel regions, and mixed regions by plane local features of the point cloud, the tassel points in the tassel sub-region, and the mixed region were the finally segmented tassel point clouds. In this study, 15 mature maize plants with 3 point cloud densities were tested. Compared with the ground truth segmented manually, the average F1 scores of the tassel segmentation were 0.763, 0.875 and 0.889 when the point cloud density was 0.8/cm, 1.3/cm, and 1.9/cm, respectively. The segmentation accuracy of this method increased with the increase of plant point cloud density. The increase of point cloud density and the number of point clouds mainly affected the calculation results of point cloud plane features in tassel segmentation. When the number of point clouds was small, the top leaf point cloud was relatively sparse. Therefore, the difference between the plane feature of the leaf point and the plane feature of the tassel point was not obvious, which led to the increase of the misclassification of the point cloud. However, the time complexity of the algorithm was O(n3), so the increase in the density and number of point clouds would lead to a significant increase in the running time. Considering the segmentation accuracy and running time, the research obtained the best effect on the mature maize plants with a point cloud density of 1.3/cm and an average number of 15,000. The segmentation F1 score reached 0.875 and the running time was 6.85 s. The results showed that this method could extract tassels from maize plant point cloud, and provided technical support for the research and application of high-throughput phenotyping and three-dimensional reconstruction of maize.

In vitro pollen germination is considered the most efficient method to assess pollen viability. The pollen germination frequency and pollen tube length, which are key indicators of pollen viability, should be accurately measured during in vitro culture. In this study, a Mask R-CNN model trained using microscopic images of tree peony (Paeonia suffruticosa) pollen has been proposed to rapidly detect the pollen germination rate and pollen tube length. To reduce the workload during image acquisition, images of synthesized crossed pollen tubes were added to the training dataset, significantly improving the model accuracy in recognizing crossed pollen tubes. At an Intersection over Union threshold of 50%, a mean average precision of 0.949 was achieved. The performance of the model was verified using 120 testing images. The R 2 value of the linear regression model using detected pollen germination frequency against the ground truth was 0.909 and that using average pollen tube length was 0.958. Further, the model was successfully applied to two other plant species, indicating a good generalizability and potential to be applied widely. [ABSTRACT FROM AUTHOR]

The Hy-Vo silent chain is a rigid rectangular frame composed of guide plate and long special pin through interference connection. The frame,which combines together internal and external combined engagement chain plate,outer meshing chain plate and short special- shaped pin,forms into a ring connected Hy-Vo silent chain. So the connecting firmness between long shaped pin and guide plate is very important. It matters to the lifetime of whole chain. The main factor influencing the connecting firmness of guide plate is the amount of interference between guide plates and special pins. When the designed amount of interference is confirmed,the precision of chain plate special hole and special pin has a very important influence on the connecting firmness. The more the precision scattering differs,the more the dispersion of connecting firmness is. By introducing the concept of equivalent diameter of the pin,the press- out force between special pin and guide plate is calculated. By comparing the calculated results with the actual test results,it is verified this method is reasonable and feasible.

The development process of engine timing system and the calculation method of timing chain tension are studied. The key technical points of main parts including timing chain,guide rail and tensioner are presented when designing the overall layout of engine timing system. According to the simulation analysis of designed engine timing chain system is carried out,the structures and load conditions of each component is improved to reach a better power transmission. Consequently,the requirements of high performance and low noise of the engine is satisfied. From the results of this study,it is concluded that this development process is reasonable and practical.

The wear property of pin is the key influence factor on automobile engine timing chain wear,the pin after cold treatment can substantially eliminate residual austenite and the carbide is refined organization,the surface hardness of pin is further improved,it plays a key role for the wear resistance of the part.

In this study, we aimed to provide an accurate method for the detection of oil and moisture content in soybeans. Introducing two-dimensional low-field nuclear magnetic resonance (LF-2D-NMR) qualitatively solved the problem of overlapping component signals that one-dimensional (1D) LF-NMR techniques cannot distinguish in soybean detection research. Soxhlet extraction, oven drying, LF-NMR spectrum, and LF-NMR oil and moisture content software were used to detect soybean oil and moisture content. The comparison showed that the LF-NMR oil and moisture content software was faster and more accurate than the other methods. The specific identification of the oil and moisture signals of soybean seeds using longitudinal relaxation time (T1) and transverse relaxation time (T2) successfully solved the problems of less mobile water, overlapping free water, and oil signals. Therefore, LF-2D-NMR can complement conventional LF-NMR assays, and this study provides a new method for the analysis and detection of moisture and oil in soybeans. [ABSTRACT FROM AUTHOR]

The wear test of 05 CT automobile engine timing chain of slit sleeve and seamless sleeve is carried out,the results show that,under the same experimental conditions,the pin and sleeves of two different forms all have cyclic softening phenomenon more or less after the chain went through high-speed wear test,and the softening degree of slit sleeve is less than that of the seamless sleeve. Under the condition of oil jet lubrication,the lubrication and cooling condition of slit sleeve chain is better than that of seamless sleeve chain,and the wear resistance of slit sleeve is better than that of seamless sleeve.

Abstract: The hydrogen abstraction and displacement process of OH radicals with CHF2CF2OCH3 (R1) and CH2FCF2OCH3 (R2) are studied theoretically. Moreover, the secondary reactions of their products (CHF2CF2OCH2, CF2CF2OCH3, CH2FCF2OCH2, and CHFCF2OCH3) with OH radical are also carried out. Electronic structures of all stationary points are calculated at the BMK/6-311+G(d,p) level. And the single point energy calculation is performed using BMC-CCSD method to refine the reaction enthalpy and barrier height for each reaction channel. The correlation between the barrier height and the corresponding bond dissociation energy is studied. Using the canonical variational transition-state theory (CVT) including the small-curvature tunneling (SCT) correction, the rate constants for CHF2CF2OCH3/CH2FCF2OCH3 +OH reactions are calculated within 200–2000K. The total rate constants calculated from the sum of the individual rate constants taking into account the Boltzmann distribution of each conformer. A good agreement is obtained between theoretical and experimental rate constants. Finally, the theoretical rate constants are fitted to four-parameter expression to assist further experimental study. [Copyright &y& Elsevier]

Dual-level direct dynamics method is used to study the kinetic properties of the hydrogen abstraction reactions of CH3CHBr + HBr → CH3CH2Br + Br (R1) and CH3CBr2 + HBr → CH3CHBr2 + Br (R2). Optimized geometries and frequencies of all the stationary points and extra points along the minimum-energy path are obtained at the MPW1K/6-311+G(d,p), MPW1K/ma-TZVP, and BMK/6-311+G(d,p) levels. Two complexes with energies less than that of the reactants are located in the entrance of each reaction at the MPW1K/6-311+G(d,p) and MPW1K/ma-TZVP levels, respectively. The energy profiles are further refined with the interpolated single-point energies method at the G2M(RCC5)//MPW1K/6-311+G(d,p) level of theory. By the improved canonical variational transition-state theory with the small-curvature tunneling correction (SCT), the rate constants are evaluated over a wide temperature range of 200-2000 K. Our calculations have shown that the radical reactivity decreases from CH3CHBr to CH3CBr2. Finally, the total rate constants are fitted by two modified Arrhenius expression. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Highlights: [•] Ground-state geometric structures of all species are optimized at M06 level of theory. [•] The optical properties of all species are calculated by means of TD-M06 method. [•] Detailed analysis for electronic transitions is performed to elucidate the UV spectra. [Copyright &y& Elsevier]

Objective: To explore the significance of multimodal monitoring in the monitoring and treatment of neurocritical care patients., Methods: 104 neurocritical care patients admitted to the department of Critical Care Medicine of Fujian Provincial Hospital from March 2019 to January 2020 were enrolled. Patients were randomly assigned into two groups, with 52 in each group. In the routine monitoring treatment group, heart rate, blood pressure, respiratory rate and the changes in consciousness and pupils were monitored after operation. The patients were treated with routine medicine to reduce intracranial pressure (ICP), maintain proper cerebral perfusion pressure (CPP), balance fluid intake and output, and maintain the airway clear. Patients in the multimodal monitoring treatment group were treated with invasive ICP monitoring, ultrasound to assess brain structure, ultrasound to measure optic nerve sheath diameter (ONSD), transcranial color doppler (TCCD), internal jugular venous blood oxygen saturation monitoring, near-infrared spectroscopy (NIRS), non-invasive cerebral blood oxygen saturation monitoring and quantitative electroencephalogram monitoring. According to the monitoring results, the patients were given targeted treatment with the goal of controlling ICP and improving brain metabolism. The length of intensive care unit (ICU) stay, the incidences of neurological complications (secondary cerebral infarction, cerebral hemorrhage, high intracranial pressure, etc.), and the incidences of poor prognosis [6 months after the onset of Glasgow outcome score (GOS) 1 to 3] were compared between the two groups. Spearman rank correlation analysis of the correlation between invasive ICP and the ICP value which was calculated by TCCD. The receiver operating characteristic (ROC) curve of invasive ICP and pulsatility index of middle cerebral artery (PI MCA ) were used to predict poor prognosis., Results: The length of ICU stay in the multimodal monitoring treatment group was significantly shorter than that of the routine monitoring treatment group (days: 6.27±3.81 vs. 9.61±5.09, P < 0.01), and the incidence of neurological complications was significantly lower than that in the routine monitoring treatment group (9.62% vs. 25.00%, P < 0.05). In the multimodal monitoring treatment group, 37 cases had a good prognosis and 15 cases had a poor prognosis, while the routine monitoring treatment group had a good prognosis in 27 cases and a poor prognosis in 25 cases. The incidence of poor prognosis in the multimodal monitoring treatment group was lower than that of the routine monitoring treatment group (28.85% vs. 48.08%, P < 0.05). In the multimodal monitoring treatment group, the invasive ICP and PI MCA of patients with good prognosis were significantly lower than those of patients with poor prognosis [invasive ICP (mmHg, 1 mmHg = 0.133 kPa): 16 (12, 17) vs. 22 (20, 24), PI MCA : 0.90±0.33 vs. 1.39±0.58, both P < 0.01]. There was no significant difference in resistance index of the middle cerebral artery (RI MCA ) between the good prognosis group and the poor prognosis group (0.63±0.12 vs. 0.66±0.15, P > 0.05). There was a positive correlation between the invasive ICP and the ICP value which was calculated by TCCD (r = 0.767, P < 0.001). ROC curve analysis showed that the area under ROC curve (AUC) of invasive ICP for poor prognosis prediction was 0.906, the best cut-off value was ≥ 18 mmHg, the sensitivity was 86.49%, and the specificity was 86.67%. The AUC of PIMCA for poor prognosis prediction was 0.759, the best cut-off value was ≥ 1.12, the sensitivity was 81.08%, and the specificity was 60.00%. The AUC of invasive ICP was greater than PI MCA (Z = 2.279, P = 0.023)., Conclusions: Comprehensive analysis of multimodal monitoring indicators for neurocritical care patients to guide clinical treatment can reduce the length of hospital stay, and reduce the risk of neurosurgery complications and disability; invasive ICP can predict poor prognosis of neurocritical care patients.