Optimal design of blade parameters for fracturing tea-picking machine

The blade is one of the most critical components in the fracturing tea-picking machine, and this study is conducted to optimize the blade's working parameters. In this study, the effects of blade width, blade thickness, and cutting angle on the maximum fracturing force of tea stems were analyzed using the L9 (34) standard orthogonal table, with the maximum fracturing force used as the evaluation index. The results indicate that the main factors affecting the maximum fracturing force (MFF) of tea stems are cutting angle (CA), blade width (BW), and blade thickness (BT) in that order. Furthermore, microscopic observation of the fracture surface revealed that compared with the thickness of the other two blades, the thickness of 0 mm caused the cross-section uneven and had lots of burrs, correspondingly resulting in the section's oxidation and the deterioration of tea leaf quality. Therefore, the optimal combination of design parameters was a cutting angle of 90°, a blade width of 2.0 mm, and a blade thickness of 0.5 mm. The findings of this study can provide reference for blade design to reduce the fracturing force of tea-picking machines, lower the working power consumption, and improve the quality of freshly plucked tea leaves

GmGBP1, a homolog of human ski interacting protein in soybean, regulates flowering and stress tolerance in Arabidopsis

BACKGROUND: SKIP is a transcription cofactor in many eukaryotes. It can regulate plant stress tolerance in rice and Arabidopsis. But the homolog of SKIP protein in soybean has been not reported up to now. RESULTS: In this study, the expression patterns of soybean GAMYB binding protein gene (GmGBP1) encoding a homolog of SKIP protein were analyzed in soybean under abiotic stresses and different day lengths. The expression of GmGBP1 was induced by polyethyleneglycol 6000, NaCl, gibberellin, abscisic acid and heat stress. GmGBP1 had transcriptional activity in C-terminal. GmGBP1 could interact with R2R3 domain of GmGAMYB1 in SKIP domain to take part in gibberellin flowering pathway. In long-day (16 h-light) condition, transgenic Arabidopsis with the ectopic overexpression of GmGBP1 exhibited earlier flowering and less number of rosette leaves; Suppression of AtSKIP in Arabidopsis resulted in growth arrest, flowering delay and down-regulation of many flowering-related genes (CONSTANS, FLOWERING LOCUS T, LEAFY); Arabidopsis myb33 mutant plants with ectopic overexpression of GmGBP1 showed the same flowering phenotype with wild type. In short-day (8 h-light) condition, transgenic Arabidopsis plants with GmGBP1 flowered later and showed a higher level of FLOWERING LOCUS C compared with wild type. When treated with abiotic stresses, transgenic Arabidopsis with the ectopic overexpression of GmGBP1 enhanced the tolerances to heat and drought stresses but reduced the tolerance to high salinity, and affected the expressions of several stress-related genes. CONCLUSIONS: In Arabidopsis, GmGBP1 might positively regulate the flowering time by affecting CONSTANS, FLOWERING LOCUS T, LEAFY and GAMYB directly or indirectly in photoperiodic and gibberellin pathways in LDs, but GmGBP1 might represse flowering by affecting FLOWERING LOCUS C and SHORT VEGETATIVE PHASE in autonomous pathway in SDs. GmGBP1 might regulate the activity of ROS-eliminating to improve the resistance to heat and drought but reduce the high-salinity tolerance

Automatic detection of low surface brightness galaxies from SDSS images

Low surface brightness (LSB) galaxies are galaxies with central surface brightness fainter than the night sky. Due to the faint nature of LSB galaxies and the comparable sky background, it is difficult to search LSB galaxies automatically and efficiently from large sky survey. In this study, we established the Low Surface Brightness Galaxies Auto Detect model (LSBG-AD), which is a data-driven model for end-to-end detection of LSB galaxies from Sloan Digital Sky Survey (SDSS) images. Object detection techniques based on deep learning are applied to the SDSS field images to identify LSB galaxies and estimate their coordinates at the same time. Applying LSBG-AD to 1120 SDSS images, we detected 1197 LSB galaxy candidates, of which 1081 samples are already known and 116 samples are newly found candidates. The B-band central surface brightness of the candidates searched by the model ranges from 22 mag arcsec $^ {- 2}$ to 24 mag arcsec $^ {- 2}$, quite consistent with the surface brightness distribution of the standard sample. 96.46\% of LSB galaxy candidates have an axis ratio ($b/a$) greater than 0.3, and 92.04\% of them have $fracDev\_r$\textless 0.4, which is also consistent with the standard sample. The results show that the LSBG-AD model learns the features of LSB galaxies of the training samples well, and can be used to search LSB galaxies without using photometric parameters. Next, this method will be used to develop efficient algorithms to detect LSB galaxies from massive images of the next generation observatories.Comment: 11 pages, 9 figures,accepted to be published on MNRA

The incidence of liver injury in Uyghur patients treated for TB in Xinjiang Uyghur autonomous region, China, and its association with hepatic enzyme polymorphisms nat2, cyp2e1, gstm1 and gstt1.

BACKGROUND AND OBJECTIVE: Of three first-line anti-tuberculosis (anti-TB) drugs, isoniazid is most commonly associated with hepatotoxicity. Differences in INH-induced toxicity have been attributed to genetic variability at several loci, NAT2, CYP2E1, GSTM1and GSTT1, that code for drug-metabolizing enzymes. This study evaluated whether the polymorphisms in these enzymes were associated with an increased risk of anti-TB drug-induced hepatitis in patients and could potentially be used to identify patients at risk of liver injury. METHODS AND DESIGN: In a cross-sectional study, 2244 tuberculosis patients were assessed two months after the start of treatment. Anti-TB drug-induced liver injury (ATLI) was defined as an ALT, AST or bilirubin value more than twice the upper limit of normal. NAT2, CYP2E1, GSTM1 and GSTT1 genotypes were determined using the PCR/ligase detection reaction assays. RESULTS: 2244 patients were evaluated, there were 89 cases of ATLI, a prevalence of 4% 9 patients (0.4%) had ALT levels more than 5 times the upper limit of normal. The prevalence of ATLI was greater among men than women, and there was a weak association with NAT2*5 genotypes, with ATLI more common among patients with the NAT2*5*CT genotype. The sensitivity of the CT genotype for identifying patients with ATLI was 42% and the positive predictive value 5.9%. CT ATLI was more common among slow acetylators (prevalence ratio 2.0 (95% CI 0.95,4.20) )compared to rapid acetylators. There was no evidence that ATLI was associated with CYP2E1 RsaIc1/c1genotype, CYP2E1 RsaIc1/c2 or c2/c2 genotypes, or GSTM1/GSTT1 null genotypes. CONCLUSIONS: In Xinjiang Uyghur TB patients, liver injury was associated with the genetic variant NAT2*5, however the genetic markers studied are unlikely to be useful for screening patients due to the low sensitivity and low positive predictive values for identifying persons at risk of liver injury

Electrical Stimulation to Conductive Scaffold Promotes Axonal Regeneration and Remyelination in a Rat Model of Large Nerve Defect

BACKGROUND: Electrical stimulation (ES) has been shown to promote nerve regeneration when it was applied to the proximal nerve stump. However, the possible beneficial effect of establishing a local electrical environment between a large nerve defect on nerve regeneration has not been reported in previous studies. The present study attempted to establish a local electrical environment between a large nerve defect, and examined its effect on nerve regeneration and functional recovery. METHODOLOGY/FINDINGS: In the present study, a conductive scaffold was constructed and used to bridge a 15 mm sciatic nerve defect in rats, and intermittent ES (3 V, 20 Hz) was applied to the conductive scaffold to establish an electrical environment at the site of nerve defect. Nerve regeneration and functional recovery were examined after nerve injury repair and ES. We found that axonal regeneration and remyelination of the regenerated axons were significantly enhanced by ES which was applied to conductive scaffold. In addition, both motor and sensory functional recovery was significantly improved and muscle atrophy was partially reversed by ES localized at the conductive scaffold. Further investigations showed that the expression of S-100, BDNF (brain-derived neurotrophic factor), P0 and Par-3 was significantly up-regulated by ES at the conductive scaffold. CONCLUSIONS/SIGNIFICANCE: Establishing an electrical environment with ES localized at the conductive scaffold is capable of accelerating nerve regeneration and promoting functional recovery in a 15 mm nerve defect in rats. The findings provide new directions for exploring regenerative approaches to achieve better functional recovery in the treatment of large nerve defect

A COVID-19 Risk Score Combining Chest CT Radiomics and Clinical Characteristics to Differentiate COVID-19 Pneumonia From Other Viral Pneumonias

With the continued transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world, identification of highly suspected COVID-19 patients remains an urgent priority. In this study, we developed and validated COVID-19 risk scores to identify patients with COVID-19. In this study, for patient-wise analysis, three signatures, including the risk score using radiomic features only, the risk score using clinical factors only, and the risk score combining radiomic features and clinical variables, show an excellent performance in differentiating COVID-19 from other viral-induced pneumonias in the validation set. For lesion-wise analysis, the risk score using three radiomic features only also achieved an excellent AUC value. In contrast, the performance of 130 radiologists based on the chest CT images alone without the clinical characteristics included was moderate as compared to the risk scores developed. The risk scores depicting the correlation of CT radiomics and clinical factors with COVID-19 could be used to accurately identify patients with COVID-19, which would have clinically translatable diagnostic and therapeutic implications from a precision medicine perspective

Parametric Surface Modelling for Tea Leaf Point Cloud Based on Non-Uniform Rational Basis Spline Technique

Plant leaf 3D architecture changes during growth and shows sensitive response to environmental stresses. In recent years, acquisition and segmentation methods of leaf point cloud developed rapidly, but 3D modelling leaf point clouds has not gained much attention. In this study, a parametric surface modelling method was proposed for accurately fitting tea leaf point cloud. Firstly, principal component analysis was utilized to adjust posture and position of the point cloud. Then, the point cloud was sliced into multiple sections, and some sections were selected to generate a point set to be fitted (PSF). Finally, the PSF was fitted into non-uniform rational B-spline (NURBS) surface. Two methods were developed to generate the ordered PSF and the unordered PSF, respectively. The PSF was firstly fitted as B-spline surface and then was transformed to NURBS form by minimizing fitting error, which was solved by particle swarm optimization (PSO). The fitting error was specified as weighted sum of the root-mean-square error (RMSE) and the maximum value (MV) of Euclidean distances between fitted surface and a subset of the point cloud. The results showed that the proposed modelling method could be used even if the point cloud is largely simplified (RMSE < 1 mm, MV < 2 mm, without performing PSO). Future studies will model wider range of leaves as well as incomplete point cloud

Investigation on the Bending Behavior of Tea Stalks Based on Non-Prismatic Beam with Virtual Internodes

The study aims to fully explicate the bending behavior of tea stalks under the condition of large deflection, which is crucial to improve the working performance of mechanized harvesting equipment. The mechanical model of the stalk was assumed to be a non-prismatic beam with virtual internodes that could differ from actual internodes. With the model, the stalk can be freely divided into multiple virtual internodes, whose flexural rigidities can be determined by solving an optimization problem, and deflection curves can be predicted after determining the positions of virtual nodes under given loads. Moreover, a novel method was proposed to obtain the deflection curve of the stalk based on the techniques of binocular vision and non-uniform rational B-spline (NURBS) curve fitting. The results show that R-squared values of fitted 2nd-degree NURBS curves of bending shape of tea stalks range from 0.9576 to 0.9964, with an average of 0.9797. The results indicate that flexural rigidity decreases from the bottom to the top of the tea stalk, and the deflection curve could be predicted more precisely with the model of piecewise flexural rigidities than that of average flexural rigidity. The study could be applied to the optimization design of the cutter and adaptive adjustment techniques of operational parameters for tea picking machines

Accuracy improvement of the immersed boundary–lattice Boltzmann coupling scheme by iterative force correction

The non-slip boundary condition at solid walls cannot be accurately achieved by the conventional immersed boundary–lattice Boltzmann (IB–LB) coupling schemes due to insufficient interpolation accuracy. To solve this problem, an iterative force correction procedure for the IB–LB coupling scheme is proposed. Cheng’s external forcing term in the LB equation is selected to properly incorporate the present and the next time step effects. The unknown IB force and the corresponding force on fluid at the next time step are calculated by iterative correction, based on the known immersed boundary speed, flow velocity, and the relationship between the IB speed and the IB force. Instead of the Dirac delta function, the Lagrange interpolation polynomial is used to obtain the IB speed from nearby fluid velocity. Typical cases, including the flow around a circular cylinder, shearing flow near a non-slip wall, and circular Couette flow between two inversely rotating cylinders, are simulated to verify and validate the method. It is shown that the present method guarantees the non-slip boundary condition and maintain the overall first-order spatial convergence rate of the conventional immersed boundary method (IBM). The accuracy improvement is obvious for both stationary and moving solid boundaries in both viscous flows and strong shearing flows. To demonstrate application possibility, a mechanical heart valve flow is also simulated, and better agreements with experimental data are achieved compared to those by commercial software