Richards Model Research Articles

Evaluation of dry matter accumulation in triticale by different sigmoidal growth models in west anatolia of turkey

Monitoring biological growth of field crops is important for planning and timing agricultural practices. In order to assess biological growth pattern of dry matter accumulation in triticale Egeyildizi triticale variety were grown in ?anakkale conditions in 2012-2013 and 2013-2014 growing seasons with continuous plant samplings from seedling emergence until seed maturation. Gompertz, Logistic, Logistic Power and Richards growth models are fitted to actual growth data and their predictions were compared. Results suggested that all sigmoidal growth models successfully explained triticale dry matter accumulation over 98 % R2 values and low mean square errors, Richards model fitted best for both years with an R2 value over 99 %. Dry matter accumulation were also investigated as a result of average temperature, precipitation, growth degree days and cumulative growth degree days with stepwise regression. Rresults indicated that average weather temperature had a similar pattern across both growing seasons and had a major influence on dry matter accumulation. Since Richards sigmoidal growth model may be adequately described growth pattern of triticale by generally high R2 with lower Mean Square Error (MSE) values.

Caracterización del crecimiento de truchas arcoiris (oncorhynchus mykiss) en el Lago Titicaca mediante modelos no lineales

This research was carried out with the objective of characterizing the growth of rainbow trout (Oncorhynchus mykiss) in Lake Titicaca using nonlinear models, from which points of biological and economic interest were identified, as well as predictions of food requirements to improve the productive and economic performance. The information used corresponds to the company Perú Pacífico located in the district of Capachica, province of Puno. The models analyzed were Logistic, Gompertz and Richards that were estimated using SAS ® NLIN and the Marquardt algorithm. The Richards model showed a higher coefficient of determination (R2). That is, it adequately describes and predicts trout growth in Lake Titicaca, under specific management conditions. The Logistic and Gompertz models showed lower predictive capacity when overestimating and underestimating the weight in the initial phase of growth, while in the final phase, they underestimate and overestimate, respectively. The growth profile shows slow weight increases in the adaptation phase to the environment, accelerated to the point of inflection, tends toward an asymptotic value as it approaches adulthood, and has a sigmoid shape, typical in trout. Finally, it has been determined the period of adaptation to the environment, the point of inflection, the time in which they would reach commercial weight (200, 250, 330 and 500 gr), and the requirement of food at certain times of a productive cycle of 269 days.

Obtaining soil hydraulic parameters from soil water content data assimilation under different climatic/soil conditions

Obtaining reliable soil hydraulic properties is essential for correct simulations of soil water content (SWC), which is a key variable in countless applications such as agricultural management, soil remediation, aquifer protection, etc. Soil hydraulic properties can be measured in the laboratory; however, the procedures are laborious and costly, and may provide estimates different from those observed in the field. An alternative approach is to obtain soil hydraulic properties using a soil water flow model in conjunction with SWC monitoring data. The goal of the present study was to analyze the efficiency of obtaining hydraulic properties utilizing data assimilation (DA) based on the Ensemble Kalman Filter method. Two soil textures in homogeneous soil profiles, and four climatic conditions were considered; observations of soil moisture data were synthetically generated using HYDRUS-1D and subsequently perturbed by the application of the conditional multivariate normal distribution. When observed SWC varied in relatively narrow range as a consequence of the forcing imposed by dry climate atmospheric boundary conditions, data assimilation provided sets of properties that led to good Richards model performance, with the RMSE below 0.02 and/or R2 above 0.8 after a period of just 100days and above 0.98 after a period of three years in all climate/soil conditions. However, the closeness of parameters from DA to the parameters used to generate the synthetic data depended on weather conditions and soil properties. One year was adequate to obtain reliable soil hydraulic properties with data assimilation.

ICT-Based Instructional Material Development: A Study of Communication Department Students

Technology as an essential matter has been integrated in today’s education for the sake of innovative and cutting-edge medium for English language teaching (ELT). Also, the students’ demands in learning English should be accommodated since they are in relation to the specialized study or the professional required of the students. This paper attempted to explain how the process of ICT-based instructional materials for undergraduate students of Communication Department is developed. This research occupies Richards (2001) model of R and D. There were three groups participated to this research. The students ( N 50), lecturer ( N 1) and the curriculum coordinator ( N 1), from those three participants, were achieved by triangulation with respect to data collection sources. The finding shows that most of the respondents agree to use ICT-based instructional material in their learning process. It means ICT-based instructional material is proper to be implemented since the practicality and ease of usage. The feedback from the students indicates that they like the appearance of the instructional material and it attracts the students to use it to support their learning.

ICT-Based Instructional Material Development: A Study of Communication Department Students

Technology as an essential matter has been integrated in today’s education for the sake of innovative and cutting-edge medium for English language teaching (ELT). Also, the students’ demands in learning English should be accommodated since they are in relation to the specialized study or the professional required of the students. This paper attempted to explain how the process of ICT-based instructional materials for undergraduate students of Communication Department is developed. This research occupies Richards (2001) model of R and D. There were three groups participated to this research. The students (N 50), lecturer (N 1) and the curriculum coordinator (N 1), from those three participants, were achieved by triangulation with respect to data collection sources. The finding shows that most of the respondents agree to use ICT-based instructional material in their learning process. It means ICT-based instructional material is proper to be implemented since the practicality and ease of usage. The feedback from the students indicates that they like the appearance of the instructional material and it attracts the students to use it to support their learning.

Application of Richards Model on Hainan Population Growth Forecast

In this paper, the data on the Hainan population were used in the Chinese Statistical Yearbook 1998-2016 and the Hainan Statistical Yearbook. The Richards growth model was used to predict trends in population growth in Hainan by regression analysis and Mathematica software. The peak of the population of Hainan was predicted using the Richards model. As a result of the two-child policy, the impact of population growth in Hainan was studied.

Adjustment of growth models in broiler chickens

Abstract: The objective of this work was to investigate adjustments of the Gompertz, Logistic, von Bertalanffy, and Richards growth models, in male and female chickens of the Cobb 500, Ross 308, and Hubbard Flex lines. Initially, 1,800 chickens were randomly housed in 36 pens, with six replicates per lineage and sex, fed ad libitum with feed according to gender, and bred until 56 days of age. Average weekly body weight for each line and sex was used to estimate model parameters using the ordinary least squares, weighted by the inverse variance of the body weight and weighted with a first-order autocorrelated error structure. Weighted models and weighted autocorrelated error models showed different parameter values when compared with the unweighted models, modifying the inflection point of the curve and according to the adjusted coefficient of determination, and the standard deviation of the residue and Akaike information criteria exhibited optimal adjustments. Among the models studied, the Richards and the Gompertz models had the best adjustments in all situations, with more realistic parameter estimates. However, the weighted Richards model, with or without ponderation with the autoregressive first order model AR (1), exhibited the best adjustments in females and males, respectively.

Mixed-effects modeling for tree height prediction models of Oriental beech in the Hyrcanian forests

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 R2 (R adj 2 ), 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 R2 (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.

Prediction of dry matter accumulation in bitter vetch

This study was carried out in Bingol province on eastern Anatolian Region between 2013 and 2015. In this study, we obtained 14 bitter vetch genotypes from different sources. The experiment was carried our in three replications in randomized block design. Each plant was weekly measured for 6 weeks starting from germination. For each plant, plant height, fresh and dry stem weight, fresh and dry leaf weights were determined. Logistic, Richards and Weibull growth models were fitted to describe the growth pattern of the genotypes. The best fitting model criteria used were coefficient of determination and mean squared. Richards’s growth model was found to best fit the data for most of the genotypes. Logistic model was the worst fit. In Turkey, climate and soil properties have very large variations. For this, local genotypes showed large variation according to plating areas. YEREL LICE genotype showed more stable and it is the height identified all growth models than other local genotypes. However, IFVE 2923 SEL and IFVE 2977 SEL 2802 these genotypes gave positive results in different environmental conditions.

Application of the Richards Model for Settlement Prediction Based on a Bidirectional Difference-Weighted Least-Squares Method

Predictions of subgrade settlement are important in engineering construction. However, current settlement prediction methods are often unsatisfactory; therefore, the Richards model, which is widely used in the biological field, is introduced in this paper to predict subgrade settlement. To improve the prediction accuracy of soft soil subgrade settlement, the settlement properties of soft soil subgrade and the characteristics of the Richards model are analyzed, and a form of the Richards model based on the bidirectional difference-weighted least-squares (BD-WLS) method is proposed. The performance of the BD-WLS method is verified via comparison with traditional methods of parameter estimation. Moreover, a case study is used to evaluate the predictive effectiveness of the Richards model based on the optimal parameter estimation method. The results show that the Richards model can reduce the mean absolute error by 2.15% on average and improve the prediction accuracy by 22.14% on average compared to other available models. Thus, the Richards model is considered suitable for simulating and predicting the settlement of soft soil subgrade, and it has excellent application potential for settlement prediction.

Construction of Fluid - solid Coupling Model with Improved Richards - BP & Its Engineering Application

In order to study the slurry diffusion law during grouting, Richards unsaturated-saturated model was introduced, the definition of the grouting model is clear, the Richards model control equation was established, And the BP neural network was introduced, the improved fluid-solid coupling model was constructed, Through the use of saturated - unsaturated seepage flow model, As well as the overflow boundary iterative solution of the mixed boundary conditions, the free surface is calculated. Engineering practice for an example, with the aid of multi - field coupling analysis software, the diffusion law of slurry was simulated numerically. The results show that the slurry diffusion rule is affected by grouting material, initial pressure and other factors. When the slurry starts, it flows in the cracks along the upper side of the grouting hole, when the pressure gradient is reduced to the critical pressure, that is, to the lower side of the flow, when the slurry diffusion stability, and ultimately its shape like an 8. The slurry is spread evenly from the overall point of view, from the grouting mouth toward the surrounding evenly spread, it gradually reaches saturation by non-saturation, and it is not a purely saturated flow, when the slurry spread and reach a saturated state, the diffusion time is the engineering grouting time.

Continuous segregation of binary heterogeneous solids in a fast-fluidized bed

Continuous segregation of binary heterogeneous solids (different density mixtures) is carried out in a gas–solid fluidized bed to study the effects of gas velocity, solids feed rate, feed composition and density difference of solids on the separation factor (recovery of flotsam at top outlet) and the quality of the product (purity of flotsam at top outlet) in a continuous fast-fluidized bed. The holdup of the bed material is obtained in each experimental run. It is observed that the separation factor decreases with increase in solids feed rate or density difference of solids, and increases with gas velocity or proportion of flotsam in the feed. The quality of the product decreases with increase in gas velocity or solids flow rate, and increases with feed composition or density difference of solids. The experimental results show that the separation factor and the quality of the product are more sensitive to gas velocity than to other operating parameters. Empirical correlations for predicting the separation factor and quality of the product are proposed based on the Richards model for individual flotsam mass fraction in the feed, and the predictions agree satisfactorily with the present experimental data.

A fast simulation algorithm for multiple moving bottlenecks and applications in urban freight traffic management

Moving bottlenecks are moving capacity restrictions that affect traffic flows, and they can be used to describe the effects of buses and trucks in transportation networks. The computation of solutions associated with the presence of moving bottlenecks is complex, since they both influence and are influenced by surrounding traffic. In this study, we propose a fast numerical scheme that can efficiently compute the solutions to an arbitrary number of moving (and fixed) bottlenecks, for a stretch of road modeled by the Lighthill–Whitham–Richards (LWR) model. Several different moving bottlenecks can be simulated endogenously all together by means of an algorithm based on a semi-analytic Lax–Hopf formula. Since the numerical scheme is semi-analytic and requires a very low number of operations, it can be employed for traffic estimation problems where fast and accurate solutions are required. We demonstrate the capabilities of the method by implementing two alternative traffic management strategies designed to minimize the negative impacts of trucks and buses in urban environments.

Boundary coupling of microscopic and first order macroscopic traffic models

We couple, at a fixed interface, the microscopic Follow the Leader model and the macroscopic Lighthill–Whitham–Richards model, both used for describing vehicular traffic. The coupling is obtained by suitable boundary conditions. We prove existence of solutions for the corresponding Cauchy problem, by using the wave-front tracking method and classical results on ordinary differential equations.

A proposed family of Unified models for sigmoidal growth

The four-parameter Unified Richards model has been applied to the growth of different animal taxa. Traditionally researchers of animal growth have favoured three-parameter models such as the logistic, Gompertz, and von Bertalanffy models. However, the growth-rate parameters of the traditional versions of these models are incomparable, and model forms returning starting points for the curves are not available. Therefore, we have reviewed and developed the family of Unified growth models (U-models), including U-versions of the logistic, Gompertz, and von Bertalanffy models, which each have an inflection placement at a fixed percentage of the upper asymptote. Consequently, in order to accommodate for those who prefer a three-parameter model, we also deduce (show) how to derive from the U-Richards a new, generic, three-parameter U-models with any predetermined inflection placement. This means an indefinite number of U-models, which will cover inflection placements at any percentage of the upper asymptote. All U-models have been re-parameterized to exhibit a unified set of parameters, which measure the same thing cross all family members, hence these models are termed the Unified family (or simply U-family). We also discuss how to interpret parameter values and whether to restrain the asymptote to a fixed value. All U-family models can be fitted to data in either of two forms: the first where one of the parameters represents the time of inflection, and the second with a parameter representing the starting value (intersection with the x-axis). Each parameter in these models only affects a single curve-shape characteristic. We show, also by fitting the models to bird growth data, how only a complete U-Richards family of models and accompanying parameter-translation equations will guarantee that we will be able to choose a model that returns realistic values and provides a consistent interpretation of growth data. There should be no enticement to choose other tools for analysing sigmoidal growth. Traditional versions of the Gompertz, logistic, von Bertalanffy or Richard’s models found in the literature have various shortcomings.

Growth Patterns of Two Chinese Native Goose Breeds

ABStRACt To study the development rules of Chinese native geese, two breeds, Shitou and Sichuan White geese were analyzed from 0 to 12 weeks of age. The growth curves were fitted with commonly used four kinds of nonlinear models (Logistic, Gompertz, Von Bertalanffy and Richards). The results showed that the growth curves were appropriately fitted with all four models but the Logistic and Richards both had the best fitting with growth curve (R 2 >0.99). Analyzing the fitting parameters of the Logistic and Richards, we found that male Shitou had the highest adult body weight while Sichuan White female had the lowest weight. In Shitou breed, Shape parameter Predicted with Richards model was corresponded with Gompertz curve, while in Sichuan breed it was in between Gompertz and Bertalanffy. Growth parameters predicted with Logistic model was much more closed to observed value as compared others. So overall logistic was the best model to analyze the growth curve in Chinese native goose and Shitou goose had excellent growth performance when compared to Sichuan White.

Real-time parameter estimation of Zika outbreaks using model averaging.

Early prediction of the final size of any epidemic and in particular for Zika disease outbreaks can be useful for health authorities in order to plan the response to the outbreak. The Richards model is often been used to estimate epidemiological parameters for arboviral diseases based on the reported cumulative cases in single- and multi-wave outbreaks. However, other non-linear models can also fit the data as well. Typically, one follows the so called post selection estimation procedure, i.e., selects the best fitting model out of the set of candidate models and ignores the model uncertainty in both estimation and inference since these procedures are based on a single model. In this paper we focus on the estimation of the final size and the turning point of the epidemic and conduct a real-time prediction for the final size of the outbreak using several non-linear models in which these parameters are estimated via model averaging. The proposed method is applied to Zika outbreak data in four cities from Colombia, during the outbreak ocurred in 2015-2016.

New observational method for prediction of one-dimensional consolidation settlement

The Chapman–Richards model is adopted in this paper to best fit the Terzaghi's one-dimensional consolidation curve. The obtained formula fits the theoretical solution well, with a regression coefficient R2 of 0·9995 and an error of less than 2%. By adopting this model, a new method to predict the ultimate settlement and the coefficient of consolidation using monitoring settlement data is proposed. The accuracy of the proposed method is verified against oedometer test and field monitoring data. For the cases verified, the ultimate settlement predictions from the proposed method are more reliable than those from the Asaoka's method for the different range of settlement data.

Ascertaining the impact of catastrophic events on dengue outbreak: The 2014 gas explosions in Kaohsiung, Taiwan.

Infectious disease outbreaks often occur in the aftermath of catastrophic events, either natural or man-made. While natural disasters such as typhoons/hurricanes, flooding and earthquakes have been known to increase the risk of infectious disease outbreak, the impact of anthropogenic disasters is less well-understood. Kaohsiung City is located in southern Taiwan, where most dengue outbreaks had occurred in the past two decades. It is also the center of petrochemical industry in Taiwan with pipelines running underneath city streets. Multiple underground gas explosions occurred in Kaohsiung in the evening of July 31, 2014 due to chemical leaks in the pipelines. The explosions caused 32 deaths, including five firefighters and two volunteer firefighters, and injured 321 persons. Historically, dengue outbreaks in southern Taiwan occurred mostly in small numbers of around 2000 cases or less, except in 2002 with over 5000 cases. However, in the months after the gas explosions, the city reported 14528 lab-confirmed dengue cases from August to December. To investigate the possible impact, if any, of the gas explosions on this record-breaking dengue outbreak, a simple mathematical model, the Richards model, is utilized to study the temporal patterns of the spread of dengue in the districts of Kaohsiung in the proximity of the explosion sites and to pinpoint the waves of infections that had occurred in each district in the aftermath of the gas explosions. The reproduction number of each wave in each district is also computed. In the aftermath of the gas explosions, early waves occurred 4–5 days (which coincides with the minimum of human intrinsic incubation period for dengue) later in districts with multiple waves. The gas explosions likely impacted the timing of the waves, but their impact on the magnitude of the 2014 outbreak remains unclear. The modeling suggests the need for public health surveillance and preparedness in the aftermath of future disasters.

The advantages of using impact resonance test in dynamic modulus master curve construction through the abbreviated test protocol

Asphalt concrete behavior is heavily dependent on temperature and loading rate. Hence, the material is typically tested at a range of temperatures and loading frequencies to capture its properties. Results are then used to develop a master curve exhibiting material behavior at the full spectrum of loading frequencies. An abbreviated testing protocol, under AASHTO PP 61-13, proposes a practical approach for development of this master curve. In this practice, the low temperature asymptote of the master curve is dominated by the limiting maximum modulus estimated through the Hirsch model. In this study, the dynamic modulus (DM) testing coupled with impact resonance (IR) test was used to evaluate the effect of this limiting maximum modulus on construction of the asphalt concrete master curve. Three different asphalt mixtures prepared with the same gradation and binder content, but different grades of stiffness were tested. The DM testing was performed at multiple temperatures and loading frequencies. The IR tests were conducted on the same specimens at the same temperatures. Two sigmoid functions (MEPDG and Richards models), and three shift factors (Arrhenius, Williams–Landel–Ferry, and polynomial) were utilized in the analysis. Richards sigmoid function coupled with polynomial shift factor provided the best fitting accuracy to the measured data. It was observed that the limiting maximum modulus obtained from experimental data was underpredicted by that obtained from the Hirsch model. The results indicated potential benefits of the IR test as a complementary testing tool to the abbreviated DM testing protocol to reliably characterize asphalt concrete.