探讨基于“三全育人”教育理念的护理本科生SEED数字化学风建设,即以学风(style of study)建设为核心,教育(education)为驱动,在线学习(e-learning)为衔接,数字化(digitization)手段为支撑。通过数字化技术整合教育资源,优化学生的学习...探讨基于“三全育人”教育理念的护理本科生SEED数字化学风建设,即以学风(style of study)建设为核心,教育(education)为驱动,在线学习(e-learning)为衔接,数字化(digitization)手段为支撑。通过数字化技术整合教育资源,优化学生的学习行为,推动全员参与、全过程管理和全方位覆盖的学风建设模式,以提升护理本科生的学习投入度和信息素养为主要目标,为护理教育提供新的实践路径。展开更多
Developing a model for soybean seed emergence offers a tool producers could use for planting date options and in predicting seedling emergence. In this study, temperature effects on soybean seed emergence were quantif...Developing a model for soybean seed emergence offers a tool producers could use for planting date options and in predicting seedling emergence. In this study, temperature effects on soybean seed emergence were quantified, modeled, and validated. The data for seed emergence model development was generated at varying temperatures, 20°C/12°C, 25°C/17°C, 30°C/22°C, 35°C/27°C, and 40°C/32°C, on two soybean cultivars, Asgrow AG5332 and Progeny P 5333 RY. Time for 50% emergence (t50%) was recorded, and seed emergence rate (SER) was estimated as reciprocal to time at each temperature in both the cultivars. No differences were observed between the cultivars in their response to temperature. A quadratic model (QM) best described the relationship between t50% and SGR and temperature (R2 = 0.93). Two sets of experiments were conducted to validate the model. In Experiment 1, 17 time-series planting date studies with the same cultivars were used by utilizing diurnal and seasonal changes in temperature conditions. In the second experiment, sunlit growth chambers with 3 different day/night temperatures, low—20°C/12°C, optimum—30°C/22°C, and high—40°C/32°C, and 64 soybean cultivars belonging MG III, IV, and V, were used. Air temperature and t50 were recorded, and SGR was estimated in all experiments. No differences were recorded among the cultivars for t50% and SGR, but differences were observed among seeding date and temperature experiments. We tested QM and traditionally used Growing Degree Days models against the data collected in validation experiments. Both the model simulations predictions agreed closely with the observed data. Based on model statistics, R2, root mean square errors (RMSE), and comparison of observations and predictions to assess model performance, the QM model performed better than the GDD model for soybean seed emergence under a wide range of cultivars and environmental conditions.展开更多
A model for cotton seedling emergence (MaGi) based on malate synthase kinetics was evaluated. Cotton seeds were planted through the early spring and into typical planting times for the areas. Soil temperatures at seed...A model for cotton seedling emergence (MaGi) based on malate synthase kinetics was evaluated. Cotton seeds were planted through the early spring and into typical planting times for the areas. Soil temperatures at seed depth were used as inputs into MaGi and a commonly used seedling emergence model based on heat unit accumulation (DD60). Time to 50% emergence was calculated and compared with predicted emergence using MaGi and DD60. MaGi yielded predictive capability without the need to resort to lengthy experimentation required by traditional methods. The results suggest that a physiological or semi-empirical approach incorporating both enzyme kinetics and whole plant temperature responses would be useful for rapidly constructing seedling emergence models.展开更多
Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its infl...Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation（R_s） and vapor pressure deficit of the air（VPD_（air））. Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in R_s and preceded the changes in VPD_（air） both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize＇s sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and R_s in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPD_（air） in comparison with wet soil and also increase the speed by which sap flow adjusts to R_s. However, sap flow lags that were associated with R_s before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements.展开更多
Continuous adsorption experiments are conducted using fixed-bed adsorption column to evaluate the performance of the adsorbent developed (from activated tamarind seeds) for the removal of Cr(VI) from aqueous solutions...Continuous adsorption experiments are conducted using fixed-bed adsorption column to evaluate the performance of the adsorbent developed (from activated tamarind seeds) for the removal of Cr(VI) from aqueous solutions and the results obtained are validated with a model developed in this study. The effects of significant parameters such as flow rate, mass of adsorbent, and initial Cr(VI) concentration are studied and breakthrough curves are obtained. As the flow rate increases from 10 to 20 mL min-1, the breakthrough time decreases from 210 to 80 min. As the mass of adsorbent increases, breakthrough time gets delayed. The breakthrough times are obtained as 110, 115 and 210 min for 15, 20 and 25 g of activated tamarind seeds. As the initial Cr(VI) concentration increases from 100 to 200 mgL-1, the break point time decreases from 210 to 45 min. The process parameters for fixed-bed adsorption such as breakthrough time, total percentage removal of Cr(VI), adsorption exhaustion rate and fraction of unused bed length are calculated and the performance of fixed-bed adsorption column is analyzed. The mechanism for Cr(VI) adsorption on activated tamarind seeds is proposed. At low value of solution pH (= 1), the increase in Cr(VI) adsorption is due to the electrostatic attraction between positively charged groups of activated tamarind seeds and the HCrO4-. A mathematical model for fixed-bed adsorption column is proposed by incorporating the effect of velocity variation along the bed length in the existing model. Pore and surface diffusion models are used to describe the intra-particle mechanism for Cr(VI) adsorption. The breakthrough curve obtained theoretically from pore diffusion model and surface diffusion model are compared with experimental results for different operating conditions. The standard deviation values obtained for pore diffusion model and solid diffusion model are 0.111 and 0.214 respectively.展开更多
A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation...A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.展开更多
It is essential to learn the temporal and spatial concentration distributions and variations of seeding agents in cloud seeding of precipitation enhancement. A three-dimensional puff trajectory model incorporating a m...It is essential to learn the temporal and spatial concentration distributions and variations of seeding agents in cloud seeding of precipitation enhancement. A three-dimensional puff trajectory model incorporating a mesoscale nonhydrostatic model has been formulated, and is applied to simulating the transporting and diffusive characteristics of multiple line sources of seeding agents within super-cooled stratus. Several important factors are taken into consideration that affect the diffusion of seeding materials such as effects of topography and vertical wind shear, temporal and spatial variation of seeding parameters and wet deposition. The particles of seeding agents are assumed to be almost inert, they have no interaction with the particles of the cloud or precipitation except that they are washed out by precipitation. The model validity is demonstrated by the analyses and comparisons of model results, and checked by the sensitivity experiments of diffusive coefficients and atmospheric stratification. The advantage of this model includes not only its exact reflection of heterogeneity and unsteadiness of background fields, but also its good simulation of transport and diffusion of multiple line sources. The horizontal diffusion rate and the horizontal transport distance have been proposed that they usually were difficult to obtain in other models. In this simulation the horizontal diffusion rate is 0.82 m s(-1) for average of one hour, and the horizontal average transport distance reaches 65 km after 1 4 which are closely related to the background Fields.展开更多
A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale ...A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.展开更多
The response of seed germination to environmental factors can be estimated by nonlinear regression. The present study was performed to compare four nonlinear regression models(segmented, beta, beta modified, and dent-...The response of seed germination to environmental factors can be estimated by nonlinear regression. The present study was performed to compare four nonlinear regression models(segmented, beta, beta modified, and dent-like) to describe the germination rate–temperature relationships of milk thistle(Silybum marianum L.) at six constant temperatures, with the aim of identifying the cardinal temperatures and thermal times required to reach different germination percentiles. Models and statistical indices were calibrated using an iterative optimization method and their performance was compared by root mean square error(RMSE), coefficient of determination(R2) and Akaike information criterion correction(AICc). The beta model was found to be the best model for predicting the required time to reach 50% germination(D50),(R2= 0.99;RMSE = 0.004; AICc =-276.97). Based on the model outputs, the base, optimum, and maximum temperatures of seed germination were 5.19 ± 0.79, 24.01 ± 0.11, and 34.32 ± 0.36 °C,respectively. The thermal times required for 50% and 90% germination were 4.99 and7.38 degree-days, respectively.展开更多
Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, ...Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology.展开更多
This paper proposes a Full Range Gaussian Markov Random Field (FRGMRF) model for monochrome image compression, where images are assumed to be Gaussian Markov Random Field. The parameters of the model are estimated bas...This paper proposes a Full Range Gaussian Markov Random Field (FRGMRF) model for monochrome image compression, where images are assumed to be Gaussian Markov Random Field. The parameters of the model are estimated based on Bayesian approach. The advantage of the proposed model is that it adapts itself according to the nature of the data (image) because it has infinite structure with a finite number of parameters, and so completely avoids the problem of order determination. The proposed model is fitted to reconstruct the image with the use of estimated parameters and seed values. The residual image is computed from the original and the reconstructed images. The proposed FRGMRF model is redefined as an error model to compress the residual image to obtain better quality of the reconstructed image. The parameters of the error model are estimated by employing the Metropolis-Hastings (M-H) algorithm. Then, the error model is fitted to reconstruct the compressed residual image. The Arithmetic coding is employed on seed values, average of the residuals and the model coefficients of both the input and residual images to achieve higher compression ratio. Different types of textured and structured images are considered for experiment to illustrate the efficiency of the proposed model. The results obtained by the FRGMRF model are compared to the JPEG2000. The proposed approach yields higher compression ratio than the JPEG whereas it produces Peak Signal to Noise Ratio (PSNR) with little higher than the JPEG, which is negligible.展开更多
In this study the effect of initial parameters such as inlet gas temperature, initial particles temperature and gas velocity on temperature changes of solid particles and outlet gas temperature in a fluidized bed drye...In this study the effect of initial parameters such as inlet gas temperature, initial particles temperature and gas velocity on temperature changes of solid particles and outlet gas temperature in a fluidized bed dryer was studied. For testing, an experimental setup was established. With combination of air and Colza seeds belonging to D groups of the Geldart classification (Geldart, 1986) fluidization regime was carried out. With five test series with maintaining the inlet gas temperature, solid particle temperature and outlet gas temperature during time were carefully measured. To analyze these data by using regression analysis to predict solid particle and outlet gas temperature, 2 correlations on initial pa-rameters were presented. The result has shown that temperature gradients in the beginning of fluidization, is very high and therefore the exponential functions in the regression model is used to predict the temperature changes.展开更多
A study of batch and column adsorption using A. jiringa seed shell as a natural adsorbent to remove methylene blue from aqueous solution was carried out. This study aimed to determine the effectiveness of A. jiringa s...A study of batch and column adsorption using A. jiringa seed shell as a natural adsorbent to remove methylene blue from aqueous solution was carried out. This study aimed to determine the effectiveness of A. jiringa seed shell in removing methylene blue as well as to determine the isotherm and adsorption kinetics of methylene blue by A. jiringa seed shells. Parameters in the batch study showed optimum pH for adsorption was at pH 7 with the optimum contact time of 60 minutes whereas the adsorbent dose obtained was 12 g/l. The percentage removal of methylene blue increased with elevated temperature while the ionic strength reduced the adsorption capacity in the dye uptake. Langmuir isotherm was suitable for this study rather than Freundlich model due to the higher regression value: R2 = 0.9999. The most suitable kinetic model for this study was the pseudo second order, compared to pseudo first order, Elovich and intra particle with the value of regression: R2 = 0.9158. This column adsorption study used several different flow rates: 15 mL/min, 18 mL/min, 21 mL/min, 24 mL/min and 27 mL/min for 75 minutes long. The breakthrough time was lesser: 10 minutes in higher flow rates (24 mL/min and 27 mL/min), which indicated the shorter time for the adsorbent to be saturated. Thomas and Yoon & Nelson’s models were proven to be more suitable compared to Bohart-Adams model for the fixed bed adsorption study.展开更多
[Objectives] This study was conducted to explore the effects of different N application rates and densities on the growth and development of direct-seeding rape as well as on its yield.[Methods] A field experiment was...[Objectives] This study was conducted to explore the effects of different N application rates and densities on the growth and development of direct-seeding rape as well as on its yield.[Methods] A field experiment was carried out by setting five N fertilizer treatments and three density levels.[Results] Increasing seeding density and N application rate could improve the seed yield of rape. The suitable N application rate for the three densities were calculated using the fitted fertilizer efficiency models, respectively, to be 186.77, 221.35 and 236.14 kg/hm^2, at which the yields were the highest. The results showed that in this area, the seeding density of direct-seeding rape could be selected in the range of 6.0×10^5-7.5×10^5 plants/hm^2, and the suitable N application rate could be in the range of 221.35-236.14 kg/hm^2.[Conclusions] This study provides a theoretical basis for the maximization of spatial resource and efficient utilization of fertilizer.展开更多
文摘探讨基于“三全育人”教育理念的护理本科生SEED数字化学风建设,即以学风(style of study)建设为核心,教育(education)为驱动,在线学习(e-learning)为衔接,数字化(digitization)手段为支撑。通过数字化技术整合教育资源,优化学生的学习行为,推动全员参与、全过程管理和全方位覆盖的学风建设模式,以提升护理本科生的学习投入度和信息素养为主要目标,为护理教育提供新的实践路径。
文摘Developing a model for soybean seed emergence offers a tool producers could use for planting date options and in predicting seedling emergence. In this study, temperature effects on soybean seed emergence were quantified, modeled, and validated. The data for seed emergence model development was generated at varying temperatures, 20°C/12°C, 25°C/17°C, 30°C/22°C, 35°C/27°C, and 40°C/32°C, on two soybean cultivars, Asgrow AG5332 and Progeny P 5333 RY. Time for 50% emergence (t50%) was recorded, and seed emergence rate (SER) was estimated as reciprocal to time at each temperature in both the cultivars. No differences were observed between the cultivars in their response to temperature. A quadratic model (QM) best described the relationship between t50% and SGR and temperature (R2 = 0.93). Two sets of experiments were conducted to validate the model. In Experiment 1, 17 time-series planting date studies with the same cultivars were used by utilizing diurnal and seasonal changes in temperature conditions. In the second experiment, sunlit growth chambers with 3 different day/night temperatures, low—20°C/12°C, optimum—30°C/22°C, and high—40°C/32°C, and 64 soybean cultivars belonging MG III, IV, and V, were used. Air temperature and t50 were recorded, and SGR was estimated in all experiments. No differences were recorded among the cultivars for t50% and SGR, but differences were observed among seeding date and temperature experiments. We tested QM and traditionally used Growing Degree Days models against the data collected in validation experiments. Both the model simulations predictions agreed closely with the observed data. Based on model statistics, R2, root mean square errors (RMSE), and comparison of observations and predictions to assess model performance, the QM model performed better than the GDD model for soybean seed emergence under a wide range of cultivars and environmental conditions.
文摘A model for cotton seedling emergence (MaGi) based on malate synthase kinetics was evaluated. Cotton seeds were planted through the early spring and into typical planting times for the areas. Soil temperatures at seed depth were used as inputs into MaGi and a commonly used seedling emergence model based on heat unit accumulation (DD60). Time to 50% emergence was calculated and compared with predicted emergence using MaGi and DD60. MaGi yielded predictive capability without the need to resort to lengthy experimentation required by traditional methods. The results suggest that a physiological or semi-empirical approach incorporating both enzyme kinetics and whole plant temperature responses would be useful for rapidly constructing seedling emergence models.
基金support from the National Key Basic Research Program of China (2016YFC0400207)the National Natural Science Foundation of China (51439006, 91425302)the 111 Program of Introducing Talents of Discipline to Universities (B14002)
文摘Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation（R_s） and vapor pressure deficit of the air（VPD_（air））. Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in R_s and preceded the changes in VPD_（air） both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize＇s sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and R_s in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPD_（air） in comparison with wet soil and also increase the speed by which sap flow adjusts to R_s. However, sap flow lags that were associated with R_s before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements.
文摘Continuous adsorption experiments are conducted using fixed-bed adsorption column to evaluate the performance of the adsorbent developed (from activated tamarind seeds) for the removal of Cr(VI) from aqueous solutions and the results obtained are validated with a model developed in this study. The effects of significant parameters such as flow rate, mass of adsorbent, and initial Cr(VI) concentration are studied and breakthrough curves are obtained. As the flow rate increases from 10 to 20 mL min-1, the breakthrough time decreases from 210 to 80 min. As the mass of adsorbent increases, breakthrough time gets delayed. The breakthrough times are obtained as 110, 115 and 210 min for 15, 20 and 25 g of activated tamarind seeds. As the initial Cr(VI) concentration increases from 100 to 200 mgL-1, the break point time decreases from 210 to 45 min. The process parameters for fixed-bed adsorption such as breakthrough time, total percentage removal of Cr(VI), adsorption exhaustion rate and fraction of unused bed length are calculated and the performance of fixed-bed adsorption column is analyzed. The mechanism for Cr(VI) adsorption on activated tamarind seeds is proposed. At low value of solution pH (= 1), the increase in Cr(VI) adsorption is due to the electrostatic attraction between positively charged groups of activated tamarind seeds and the HCrO4-. A mathematical model for fixed-bed adsorption column is proposed by incorporating the effect of velocity variation along the bed length in the existing model. Pore and surface diffusion models are used to describe the intra-particle mechanism for Cr(VI) adsorption. The breakthrough curve obtained theoretically from pore diffusion model and surface diffusion model are compared with experimental results for different operating conditions. The standard deviation values obtained for pore diffusion model and solid diffusion model are 0.111 and 0.214 respectively.
文摘A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.
文摘It is essential to learn the temporal and spatial concentration distributions and variations of seeding agents in cloud seeding of precipitation enhancement. A three-dimensional puff trajectory model incorporating a mesoscale nonhydrostatic model has been formulated, and is applied to simulating the transporting and diffusive characteristics of multiple line sources of seeding agents within super-cooled stratus. Several important factors are taken into consideration that affect the diffusion of seeding materials such as effects of topography and vertical wind shear, temporal and spatial variation of seeding parameters and wet deposition. The particles of seeding agents are assumed to be almost inert, they have no interaction with the particles of the cloud or precipitation except that they are washed out by precipitation. The model validity is demonstrated by the analyses and comparisons of model results, and checked by the sensitivity experiments of diffusive coefficients and atmospheric stratification. The advantage of this model includes not only its exact reflection of heterogeneity and unsteadiness of background fields, but also its good simulation of transport and diffusion of multiple line sources. The horizontal diffusion rate and the horizontal transport distance have been proposed that they usually were difficult to obtain in other models. In this simulation the horizontal diffusion rate is 0.82 m s(-1) for average of one hour, and the horizontal average transport distance reaches 65 km after 1 4 which are closely related to the background Fields.
基金jointly supported by the Main Direction Program of Knowledge Innovation of the Chinese Academy of Sciences(Grant No.KZCX2EW203)the National Key Basic Research Program of China(Grant No.2013CB430105)the National Department of Public Benefit Research Foundation(Grant No.GYHY201006031)
文摘A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.
文摘The response of seed germination to environmental factors can be estimated by nonlinear regression. The present study was performed to compare four nonlinear regression models(segmented, beta, beta modified, and dent-like) to describe the germination rate–temperature relationships of milk thistle(Silybum marianum L.) at six constant temperatures, with the aim of identifying the cardinal temperatures and thermal times required to reach different germination percentiles. Models and statistical indices were calibrated using an iterative optimization method and their performance was compared by root mean square error(RMSE), coefficient of determination(R2) and Akaike information criterion correction(AICc). The beta model was found to be the best model for predicting the required time to reach 50% germination(D50),(R2= 0.99;RMSE = 0.004; AICc =-276.97). Based on the model outputs, the base, optimum, and maximum temperatures of seed germination were 5.19 ± 0.79, 24.01 ± 0.11, and 34.32 ± 0.36 °C,respectively. The thermal times required for 50% and 90% germination were 4.99 and7.38 degree-days, respectively.
基金supported by the National Basic Research Program of China (No. 2006CB101708)National Science and Technology Supporting Item of China (No. 2006BAD10A00).
文摘Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology.
文摘This paper proposes a Full Range Gaussian Markov Random Field (FRGMRF) model for monochrome image compression, where images are assumed to be Gaussian Markov Random Field. The parameters of the model are estimated based on Bayesian approach. The advantage of the proposed model is that it adapts itself according to the nature of the data (image) because it has infinite structure with a finite number of parameters, and so completely avoids the problem of order determination. The proposed model is fitted to reconstruct the image with the use of estimated parameters and seed values. The residual image is computed from the original and the reconstructed images. The proposed FRGMRF model is redefined as an error model to compress the residual image to obtain better quality of the reconstructed image. The parameters of the error model are estimated by employing the Metropolis-Hastings (M-H) algorithm. Then, the error model is fitted to reconstruct the compressed residual image. The Arithmetic coding is employed on seed values, average of the residuals and the model coefficients of both the input and residual images to achieve higher compression ratio. Different types of textured and structured images are considered for experiment to illustrate the efficiency of the proposed model. The results obtained by the FRGMRF model are compared to the JPEG2000. The proposed approach yields higher compression ratio than the JPEG whereas it produces Peak Signal to Noise Ratio (PSNR) with little higher than the JPEG, which is negligible.
文摘In this study the effect of initial parameters such as inlet gas temperature, initial particles temperature and gas velocity on temperature changes of solid particles and outlet gas temperature in a fluidized bed dryer was studied. For testing, an experimental setup was established. With combination of air and Colza seeds belonging to D groups of the Geldart classification (Geldart, 1986) fluidization regime was carried out. With five test series with maintaining the inlet gas temperature, solid particle temperature and outlet gas temperature during time were carefully measured. To analyze these data by using regression analysis to predict solid particle and outlet gas temperature, 2 correlations on initial pa-rameters were presented. The result has shown that temperature gradients in the beginning of fluidization, is very high and therefore the exponential functions in the regression model is used to predict the temperature changes.
文摘A study of batch and column adsorption using A. jiringa seed shell as a natural adsorbent to remove methylene blue from aqueous solution was carried out. This study aimed to determine the effectiveness of A. jiringa seed shell in removing methylene blue as well as to determine the isotherm and adsorption kinetics of methylene blue by A. jiringa seed shells. Parameters in the batch study showed optimum pH for adsorption was at pH 7 with the optimum contact time of 60 minutes whereas the adsorbent dose obtained was 12 g/l. The percentage removal of methylene blue increased with elevated temperature while the ionic strength reduced the adsorption capacity in the dye uptake. Langmuir isotherm was suitable for this study rather than Freundlich model due to the higher regression value: R2 = 0.9999. The most suitable kinetic model for this study was the pseudo second order, compared to pseudo first order, Elovich and intra particle with the value of regression: R2 = 0.9158. This column adsorption study used several different flow rates: 15 mL/min, 18 mL/min, 21 mL/min, 24 mL/min and 27 mL/min for 75 minutes long. The breakthrough time was lesser: 10 minutes in higher flow rates (24 mL/min and 27 mL/min), which indicated the shorter time for the adsorbent to be saturated. Thomas and Yoon & Nelson’s models were proven to be more suitable compared to Bohart-Adams model for the fixed bed adsorption study.
文摘[Objectives] This study was conducted to explore the effects of different N application rates and densities on the growth and development of direct-seeding rape as well as on its yield.[Methods] A field experiment was carried out by setting five N fertilizer treatments and three density levels.[Results] Increasing seeding density and N application rate could improve the seed yield of rape. The suitable N application rate for the three densities were calculated using the fitted fertilizer efficiency models, respectively, to be 186.77, 221.35 and 236.14 kg/hm^2, at which the yields were the highest. The results showed that in this area, the seeding density of direct-seeding rape could be selected in the range of 6.0×10^5-7.5×10^5 plants/hm^2, and the suitable N application rate could be in the range of 221.35-236.14 kg/hm^2.[Conclusions] This study provides a theoretical basis for the maximization of spatial resource and efficient utilization of fertilizer.
