Constructing G2 Continuous Curve on Freeform Surface with Normal Projection

AbstractThis article presents a new method for G2 continuous interpolation of an arbitrary sequence of points on an implicit or parametric surface with prescribed tangent direction and curvature vector, respectively, at every point. First, a G2 continuous curve is constructed in three-dimensional space. Then the curve is projected normally onto the given surface. The desired interpolation curve is just the projection curve, which can be obtained by numerically solving the initial- value problems for a system of first-order ordinary differential equations in the parametric domain for parametric case or in three-dimensional space for implicit case. Several shape parameters are introduced into the resulting curve, which can be used in subsequent interactive modification so that the shape of the resulting curve meets our demand. The presented method is independent of the geometry and parameterization of the base surface. Numerical experiments demonstrate that it is effective and potentially useful in numerical control (NC) machining, path planning for robotic fibre placement, patterns design on surface and other industrial and research fields

β-Elemene alleviates bone cancer-related pain in rats by modulating N-methyl-D-aspartate receptor 2B subunit

Purpose: To investigate the effect of β-elemene on bone cancer-related pain (BCRP) and its underlying mechanism in a rat model.Methods: A rat model of BCRP was established by injection of Walker 256 cells into the medullary cavity in adult male Sprague-Dawley rats. The effects of β-elemene on pain-related behaviours were assessed by paw withdrawal mechanical threshold (PWMT) and paw withdrawal thermal latency (PWTL). Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were used to analyse the transcription and translation levels of N-methyl-D-aspartate receptor 2B subunit (NR2B), respectively.Results: This study found that PWMT and PWTL were significantly decreased in rats as evidence of successful establishment of a rat model of BCRP. Behavioral test showed that β-elemene treatment could attenuate pain-related behaviours. This analgesic effect began 1 h after drug injection, reached the highest value at 2 h, declined at 4 h, and disappeared by 24 h. qRT-PCR and western blotting indicated that intrathecal administration of β-elemene down-regulated mRNA and protein levels of NR2B.Conclusion: The results show that β-elemene alleviates behaviours related to pain in a rat model of BCRP probably by modulating NR2B, thus indicating a new potential treatment method for cancerrelated pain.Keywords: β-Elemene, Bone cancer, Pain relief, N-methyl-D-aspartate receptor 2B subunit (NR2B), Sensitisatio

Constructing G2 Continuous Curve on Freeform Surface with Normal Projection

AbstractThis article presents a new method for G2 continuous interpolation of an arbitrary sequence of points on an implicit or parametric surface with prescribed tangent direction and curvature vector, respectively, at every point. First, a G2 continuous curve is constructed in three-dimensional space. Then the curve is projected normally onto the given surface. The desired interpolation curve is just the projection curve, which can be obtained by numerically solving the initial- value problems for a system of first-order ordinary differential equations in the parametric domain for parametric case or in three-dimensional space for implicit case. Several shape parameters are introduced into the resulting curve, which can be used in subsequent interactive modification so that the shape of the resulting curve meets our demand. The presented method is independent of the geometry and parameterization of the base surface. Numerical experiments demonstrate that it is effective and potentially useful in numerical control (NC) machining, path planning for robotic fibre placement, patterns design on surface and other industrial and research fields

A simple high-performance current control strategy for V2G three-phase four-leg inverter with LCL filter

Electric vehicles (EVs) can behave as distributed energy storage devices for providing on-demand smart grid support service, that is an emerging Vehicle-to-Grid (V2G) technology. A high-performance and easy-implementation current control strategy for V2G Three-phase four-leg inverter with LCL filter is proposed. It consists of a deadbeat (DB) controller and a paralleled repetitive controller (RC). The DB controller is based on weighted average inductor current (WAIC) scheme, which simplifies the third-order LCL filter to be an equivalent 1st order L filter. The stability of the DB controlled inverter with the unmodelled system time delay is analyzed. DB controller is of very fast response and easy implementation, but is not immune to system time delay and various uncertainties. To overcome the disadvantages, a plug-in RC is added to reinforce the DB controller to remove harmonic distortion from the feed-in current in the presence of parameter uncertainties. A lab prototype of 10kW grid-connected three-phase four-leg inverter has been built up to validate the proposed current control strategy. The simulations and experiments are provided to demonstrate the validity of the proposed control strategy

Growth Rate and Leaf Functional Traits of Four Broad-Leaved Species Underplanted in Chinese Fir Plantations with Different Tree Density Levels

The close-to-Nature management method of interplanting broad-leaved trees after thinning of monoculture plantations is an important mixed species restoration model to improve the ecological service and functions effectively as well as to reduce the productivity decline of the multi-generation continuous planting of monoculture. Thus, the selection of tree species for establishing mixed forest and its ecological adaptability are the key issues. In this study, we conducted thinning experiment in an 11-year-old Chinese fir plantation with retention density of 900 trees/ha, 1200 trees/ha and 1875 trees/ha, and then underplanted four broad-leaved species, Schima superba, Phoebe bournei, Tsoongiodendron odorum and Michelia macclurei. After three years, we analyzed the growth rate and leaf functional traits of the broad-leaved species and their correlations with stand characteristics. The results showed that growth rate of seedlings of the four broad-leaved species were significantly different (p < 0.05) among different tree density levels and species. Low tree density favored seedling growth compared with high tree density and seedlings of T. odorum and S. superba performed best. However, leaf functional traits varied significantly (p < 0.01) among species only, and T. odorum had the largest specific leaf area, the smallest leaf mass per unit area, the smallest leaf tissue density, relatively large leaf thickness, and relatively small dry matter content. The leaf C content varied significantly among tree density levels and species; leaf N content varied significantly among species only; and leaf p content varied among tree density levels only. Correlation analyses between growth characters and leaf functional traits showed that height growth was significantly correlated with leaf N content (r = 0.686; p = 0.041) and with C:N ratio (r = -0.682; p = 0.043). Root collar diameter growth was significantly correlated with specific leaf area (r = 0.820; p = 0.007), leaf N content (r = 0.685; p = 0.042), leaf thickness (r = -0.706; p = 0.034) and leaf mass per unit area (r = -0.812; p = 0.008). Thus, leaf functional traits possibly predict diameter growth better than height growth. As a whole, growth rate and leaf functional traits could be used as a guide for selection of species for under planting in thinned pure monoculture plantations to establish conifer-broadleaved mixed forests. Based on growth rate and leaf functional traits, T. odorum appeared to be suitable for planting under low tree density stands where the degree of shading is low

The development of a vision-based phenotypic analysis algorithm for measuring spikelet-related traits in rice

Rice (Oryza sativa) and its production is of great importance to China’s food security. To assess its yield potential and grain quality, spikelet-related traits such as the number of spikelets per spike, seed coat color, spikelet length, width and length, and width ratio (W/L ratio) can be employed as key phenotypic evidence. Nevertheless, the present methods for spikelet-related trait analysis are still largely relying on manual counting or various post-harvest grain testing equipment, which is time-consuming, prone to error, and costly. Here, we present an original phenotypic analysis algorithm that can analyze key spikelet-based traits based on images collected by high-definition cameras, photo scanners, or smartphones, under both indoor and outdoor conditions. The vision-based algorithm combines automated image processing and deep learning techniques with domain knowledge in rice spikelet measurement, which does not require any prerequisites such as threshing or post-harvest processing. Besides the number of spikelets per spike, the algorithm can quickly detect and measure complete rice spikelets from the acquired images, quantifying spikelet-related traits such as grain length, grain width, W/L ratio, circularity, and grain coat color. We chose 18 rice varieties to verify the algorithm using images collected from indoor and in-field settings. Based on the trait analysis results, we examined correlations (i.e. the coefficient of determination, R2) between the computational and manual scoring for traits such as the number of spikelets per spike and concluded significant positive correlations: R2 =0.95 (P<0.001; n=4 930 spikelets, scored from indoor images), R2=0.88 (P<0.001; n=4 191, scored from indoor rice spikelets), R2=0.86 (P<0.001; n=2 490, scored from infield images), and R2=0.85 (P<0.001; n=2 645, scored from in-field rice spikelets). Additionally, we performed correlation analysis using the W/L ratio trait and concluded strong positive correlations, R2=0.84 (P<0.001; n=1 454, scored from indoor images) and R2=0.71 (P<0.001; n=726, scored from in-field images). Both correlations indicate a mechanistic link between the algorithm-derived traits and plant specialists’ scores. The above results suggest that the work presented here is reliable for automated phenotypic analysis of spikelet-related traits in rice. Furthermore, through cluster analysis, the 18 tested rice varieties can be reliably divided into four categories based on the spikelet-related trait analysis produced by our algorithm, similar to the clustering analysis results using manual scoring. This indicates that our work can be employed to enable the identification of phenotypic variation of these rice varieties, effectively. Hence, we trust our work can have a wide range of applications to provide an original, low-cost, accurate and generalized algorithmic solution for spikelet-related trait analysis in rice, enabling biological studies in this important research domain