Effectiveness and safety of mouthguards are greatly affected by its thickness. The aim of this study was to clarify the effect of model height and model position on the forming table on the mouthguard thickness in the...Effectiveness and safety of mouthguards are greatly affected by its thickness. The aim of this study was to clarify the effect of model height and model position on the forming table on the mouthguard thickness in thermoforming using a circular frame. Mouthguards were thermoformed using 4.0-mm-thick ethylene-vinyl-acetate sheets and a vacuum forming machine. The sheet was sandwiched between circular frames and fixed to the clamp of the forming machine. Working models were two types of hard gypsum models trimmed so that the height of the anterior part was 25 mm (Model A) and 30 mm (Model B). The model was placed with its anterior rim positioned 40 mm (P40), 30 mm (P30), 20 mm (P20), or 10 mm (P10) from the front of the forming table. Differences in the reduction rate of the thickness due to the model height and model positions were analyzed by two-way ANOVA and Bonferroni’s multiple comparison test. Differences depending on the model height were observed at P40 at the incisal edge and P30, P20, and P10 on the labial surface, and the reduction rate of the thickness was significantly smaller in Model A (P < 0.01). As the distance from the model anterior rim to the front of the forming table was smaller, the rate of the thickness of the incisal edge and the labial surface decreases became larger. The rate of decrease in the thickness of the cusp and buccal surface was the smallest at P20. This study indicated that the difference in the thickness of the single-layer mouthguard depending on the model position on the forming table is affected by the model height. However, that is only the anterior part of the mouthguard, and the difference in thickness reduction rate is less than 5%. Additionally, in order to perform stable forming, it is useful to increase the distance from the model to the frame, and it is important to position the part whose thickness is desired to be maintained in the center of the forming table.展开更多
Understanding the relationship between tree height (H) and diameter at breast height (D) is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its appli...Understanding the relationship between tree height (H) and diameter at breast height (D) is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its applicability for unevenly aged stands of moso bamboo forest at a regional scale. Field data were collected for 21 plots. Based on these data, we identified two strong power relationships: a corre- lation between the mean bamboo height (Hm) and the upper mean H (Hu), and a correlation between the mean D (Din) and the upper mean D (Du). Simulation results derived from the aUometric equation model were in good agreement with observed culms derived from the field data for the 21 stands, with a root-mean-square error and relative root-mean-square error of 1.40 m and 13.41%, respectively. These results demonstrate that the allometric equation model had a strong predictive power in the unevenly aged stands at a regional scale. In addition, the estimated average height-diameter (H-D) model for South Anhui Province was used to predict H for the same type of bamboo in Hunan Province based on the measured D, and the results were highly similar. The allometric equation model has multiple uses at the regional scale, including the evaluation of the variation in the H- D relationship among regions. The model describes the average H-D relationship without considering the effects caused by variation in site conditions, tree density and other factors.展开更多
Individual Tree Detection-and-Counting(ITDC)is among the important tasks in town areas,and numerous methods are proposed in this direction.Despite their many advantages,still,the proposed methods are inadequate to pro...Individual Tree Detection-and-Counting(ITDC)is among the important tasks in town areas,and numerous methods are proposed in this direction.Despite their many advantages,still,the proposed methods are inadequate to provide robust results because they mostly rely on the direct field investigations.This paper presents a novel approach involving high-resolution imagery and the Canopy-Height-Model(CHM)data to solve the ITDC problem.The new approach is studied in six urban scenes:farmland,woodland,park,industrial land,road and residential areas.First,it identifies tree canopy regions using a deep learning network from high-resolution imagery.It then deploys the CHM-data to detect treetops of the canopy regions using a local maximum algorithm and individual tree canopies using the region growing.Finally,it calculates and describes the number of individual trees and tree canopies.The proposed approach is experimented with the data from Shanghai,China.Our results show that the individual tree detection method had an average overall accuracy of 0.953,with a precision of 0.987 for woodland scene.Meanwhile,the R2 value for canopy segmentation in different urban scenes is greater than 0.780 and 0.779 for canopy area and diameter size,respectively.These results confirm that the proposed method is robust enough for urban tree planning and management.展开更多
Fifty-three larch interspecific hybrid clones(Larix kaempferi × L.gmelini) and their parent clones were used for growth curve analysis of height variations.The growth curves of the 55 clones were 'S'-shaped a...Fifty-three larch interspecific hybrid clones(Larix kaempferi × L.gmelini) and their parent clones were used for growth curve analysis of height variations.The growth curves of the 55 clones were 'S'-shaped and 36 exhibited similar curves as the male parent.The coefficients of the logistic models were higher than 0.943,indicating that our results were effective in the simulation of the growth curves.ANOVA analysis showed significant differences in height of different clones (P/0.01).Average date of maximum height growth was Day 173,and average duration of rapid growth lasted for 50 days.Annual average increase in height was 9.7cm d^(-1) and daily average increase was 0.2 cm.The ratio of GR to the total annual increase in height ranged from 51.2 to 68.8%,with the average being 59.8%.There was a positive correlation between k values and plant heights which benefited from the evaluation of early plant height.There was also a positive correlation between GR(growth stage),GD(plant height) and annual increase in height.These results are informative to the evaluation of the elite clone selection and provide a theoretical basis for breeding and management.展开更多
Height–diameter relationships are essential elements of forest assessment and modeling efforts.In this work,two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Orient...Height–diameter relationships are essential elements of forest assessment and modeling efforts.In this work,two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Oriental beech(Fagus orientalis Lipsky) in the Hyrcanian Forest in Iran.The predictive performance of these models was first assessed by different evaluation criteria: adjusted R^2(R^2_(adj)),root mean square error(RMSE),relative RMSE(%RMSE),bias,and relative bias(%bias) criteria.The best model was selected for use as the base mixed-effects model.Random parameters for test plots were estimated with different tree selection options.Results show that the Chapman–Richards model had better predictive ability in terms of adj R^2(0.81),RMSE(3.7 m),%RMSE(12.9),bias(0.8),%Bias(2.79) than the other models.Furthermore,the calibration response,based on a selection of four trees from the sample plots,resulted in a reduction percentage for bias and RMSE of about 1.6–2.7%.Our results indicate that the calibrated model produced the most accurate results.展开更多
株高是表征作物生长状况、产量预测及进行精准管理的重要表型性状,小麦的株高监测在田间精准管理和育种栽培中具有重要科学与应用价值。该研究基于SegFormer模型,提出了一种基于双分支特征编码和多尺度特征融合解码的小麦冠层分割方法,...株高是表征作物生长状况、产量预测及进行精准管理的重要表型性状,小麦的株高监测在田间精准管理和育种栽培中具有重要科学与应用价值。该研究基于SegFormer模型,提出了一种基于双分支特征编码和多尺度特征融合解码的小麦冠层分割方法,并基于分割掩膜构建小麦高度自动估计系统。首先,在分割模型的编码器部分,采用CNN细节分支与Transformer语义分支并联结构,增强局部纹理特征和全局上下文特征的协同表达能力。其次,在解码器部分,通过逐步上采样与跳跃连接机制,实现对多尺度特征的高效融合,有效提升空间信息恢复能力与边界细节建模能力。最后,结合分割结果和作物高度模型,对180个样本小区从分蘖期至开花期的小麦冠层高度进行了估计与验证。试验结果表明,改进模型在分割任务中平均交并比(mean intersection over union,mIoU)、平均像素准确率(mean pixel accuracy,mPA)和像素准确率(pixel accuracy,PA)分别达到80.92%、89.42%和90.07%,均优于原始SegFormer模型。高度估计结果与田间实测值的决定系数(coefficient of determination,R2)为0.985,均方根误差(root mean square error,RMSE)为0.73 cm,相对均方根误差(relative RMSE,rRMSE)为2.41%。研究结果表明,该研究方法能够高效、准确地提取小麦冠层空间分布及株高信息,为冬小麦生长动态监测、田间表型研究及精准农业应用提供了可靠的技术支撑。展开更多
摘要Effectiveness and safety of mouthguards are greatly affected by its thickness. The aim of this study was to clarify the effect of model height and model position on the forming table on the mouthguard thickness in thermoforming using a circular frame. Mouthguards were thermoformed using 4.0-mm-thick ethylene-vinyl-acetate sheets and a vacuum forming machine. The sheet was sandwiched between circular frames and fixed to the clamp of the forming machine. Working models were two types of hard gypsum models trimmed so that the height of the anterior part was 25 mm (Model A) and 30 mm (Model B). The model was placed with its anterior rim positioned 40 mm (P40), 30 mm (P30), 20 mm (P20), or 10 mm (P10) from the front of the forming table. Differences in the reduction rate of the thickness due to the model height and model positions were analyzed by two-way ANOVA and Bonferroni’s multiple comparison test. Differences depending on the model height were observed at P40 at the incisal edge and P30, P20, and P10 on the labial surface, and the reduction rate of the thickness was significantly smaller in Model A (P < 0.01). As the distance from the model anterior rim to the front of the forming table was smaller, the rate of the thickness of the incisal edge and the labial surface decreases became larger. The rate of decrease in the thickness of the cusp and buccal surface was the smallest at P20. This study indicated that the difference in the thickness of the single-layer mouthguard depending on the model position on the forming table is affected by the model height. However, that is only the anterior part of the mouthguard, and the difference in thickness reduction rate is less than 5%. Additionally, in order to perform stable forming, it is useful to increase the distance from the model to the frame, and it is important to position the part whose thickness is desired to be maintained in the center of the forming table.
基金financially supported by the Special Fund for Basic Scientific Research of International Centre for Bamboo and Rattan(1632014003)National Natural Science Foundation of China(31101148 and 31300177)
摘要Understanding the relationship between tree height (H) and diameter at breast height (D) is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its applicability for unevenly aged stands of moso bamboo forest at a regional scale. Field data were collected for 21 plots. Based on these data, we identified two strong power relationships: a corre- lation between the mean bamboo height (Hm) and the upper mean H (Hu), and a correlation between the mean D (Din) and the upper mean D (Du). Simulation results derived from the aUometric equation model were in good agreement with observed culms derived from the field data for the 21 stands, with a root-mean-square error and relative root-mean-square error of 1.40 m and 13.41%, respectively. These results demonstrate that the allometric equation model had a strong predictive power in the unevenly aged stands at a regional scale. In addition, the estimated average height-diameter (H-D) model for South Anhui Province was used to predict H for the same type of bamboo in Hunan Province based on the measured D, and the results were highly similar. The allometric equation model has multiple uses at the regional scale, including the evaluation of the variation in the H- D relationship among regions. The model describes the average H-D relationship without considering the effects caused by variation in site conditions, tree density and other factors.
基金supported by the project funded by International Research Center of Big Data for Sustainable 740 Development Goals[Grant Number CBAS2022GSP07]Fundamental Research Funds for the Central Universities,Chongqing Natural Science Foundation[Grant Number CSTB2022NSCQMSX 2069]Ministry of Education of China[Grant Number 19JZD023].
摘要Individual Tree Detection-and-Counting(ITDC)is among the important tasks in town areas,and numerous methods are proposed in this direction.Despite their many advantages,still,the proposed methods are inadequate to provide robust results because they mostly rely on the direct field investigations.This paper presents a novel approach involving high-resolution imagery and the Canopy-Height-Model(CHM)data to solve the ITDC problem.The new approach is studied in six urban scenes:farmland,woodland,park,industrial land,road and residential areas.First,it identifies tree canopy regions using a deep learning network from high-resolution imagery.It then deploys the CHM-data to detect treetops of the canopy regions using a local maximum algorithm and individual tree canopies using the region growing.Finally,it calculates and describes the number of individual trees and tree canopies.The proposed approach is experimented with the data from Shanghai,China.Our results show that the individual tree detection method had an average overall accuracy of 0.953,with a precision of 0.987 for woodland scene.Meanwhile,the R2 value for canopy segmentation in different urban scenes is greater than 0.780 and 0.779 for canopy area and diameter size,respectively.These results confirm that the proposed method is robust enough for urban tree planning and management.
基金supported by Grants from the National Science and Technology Pillar Program of China(No.2015DAD09B01)
摘要Fifty-three larch interspecific hybrid clones(Larix kaempferi × L.gmelini) and their parent clones were used for growth curve analysis of height variations.The growth curves of the 55 clones were 'S'-shaped and 36 exhibited similar curves as the male parent.The coefficients of the logistic models were higher than 0.943,indicating that our results were effective in the simulation of the growth curves.ANOVA analysis showed significant differences in height of different clones (P/0.01).Average date of maximum height growth was Day 173,and average duration of rapid growth lasted for 50 days.Annual average increase in height was 9.7cm d^(-1) and daily average increase was 0.2 cm.The ratio of GR to the total annual increase in height ranged from 51.2 to 68.8%,with the average being 59.8%.There was a positive correlation between k values and plant heights which benefited from the evaluation of early plant height.There was also a positive correlation between GR(growth stage),GD(plant height) and annual increase in height.These results are informative to the evaluation of the elite clone selection and provide a theoretical basis for breeding and management.
基金This research received no specific grant from any funding agency in the public,commercial,or not-for-profit sectors
摘要Height–diameter relationships are essential elements of forest assessment and modeling efforts.In this work,two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Oriental beech(Fagus orientalis Lipsky) in the Hyrcanian Forest in Iran.The predictive performance of these models was first assessed by different evaluation criteria: adjusted R^2(R^2_(adj)),root mean square error(RMSE),relative RMSE(%RMSE),bias,and relative bias(%bias) criteria.The best model was selected for use as the base mixed-effects model.Random parameters for test plots were estimated with different tree selection options.Results show that the Chapman–Richards model had better predictive ability in terms of adj R^2(0.81),RMSE(3.7 m),%RMSE(12.9),bias(0.8),%Bias(2.79) than the other models.Furthermore,the calibration response,based on a selection of four trees from the sample plots,resulted in a reduction percentage for bias and RMSE of about 1.6–2.7%.Our results indicate that the calibrated model produced the most accurate results.
摘要株高是表征作物生长状况、产量预测及进行精准管理的重要表型性状,小麦的株高监测在田间精准管理和育种栽培中具有重要科学与应用价值。该研究基于SegFormer模型,提出了一种基于双分支特征编码和多尺度特征融合解码的小麦冠层分割方法,并基于分割掩膜构建小麦高度自动估计系统。首先,在分割模型的编码器部分,采用CNN细节分支与Transformer语义分支并联结构,增强局部纹理特征和全局上下文特征的协同表达能力。其次,在解码器部分,通过逐步上采样与跳跃连接机制,实现对多尺度特征的高效融合,有效提升空间信息恢复能力与边界细节建模能力。最后,结合分割结果和作物高度模型,对180个样本小区从分蘖期至开花期的小麦冠层高度进行了估计与验证。试验结果表明,改进模型在分割任务中平均交并比(mean intersection over union,mIoU)、平均像素准确率(mean pixel accuracy,mPA)和像素准确率(pixel accuracy,PA)分别达到80.92%、89.42%和90.07%,均优于原始SegFormer模型。高度估计结果与田间实测值的决定系数(coefficient of determination,R2)为0.985,均方根误差(root mean square error,RMSE)为0.73 cm,相对均方根误差(relative RMSE,rRMSE)为2.41%。研究结果表明,该研究方法能够高效、准确地提取小麦冠层空间分布及株高信息,为冬小麦生长动态监测、田间表型研究及精准农业应用提供了可靠的技术支撑。