507 research outputs found
A site-specific and dynamic modeling system for zoning and optimizing variable rate irrigation in cotton
Cotton irrigation has been rapidly expanding in west Tennessee during the past decade. Variable rate irrigation is expected to enhance water use efficiency and crop yield in this region due to the significant field-scale soil spatial heterogeneity. A detailed understanding of the soil available water content within the effective root zone is needed to optimally schedule irrigation. In addition, site-specific crop-yield mathematical relationships should be established to identify optimum irrigation management. This study aimed to design and evaluate a site-specific modeling system for zoning and optimizing variable rate irrigation in cotton. The specific objectives of this study were to investigate (i) the spatial variability of soil attributes at the field-scale, (ii) site-specific cotton lint yieldwater relationships across all soil types, and (iii) multiple zoning strategies for variable rate irrigation scenarios. The field (73 ha) was sampled and apparent soil electrical conductivity (ECa) was measured. Landsat 8 satellite data was acquired, processed, and transformed to compare indicators of vegetation and soil response to cotton lint yields, variable irrigation rates, and the spatial variability of soil attributes. Multiple modeling scenarios were developed and examined. Although experiments were performed during two wet years, supplemental irrigation enhanced cotton yield across all soil types in comparison with rain-fed conditions. However, length of cropping season and rainfall distribution remarkably affected cotton response to supplemental irrigation. Geostatistical analysis showed spatial variability in soil textural components and water content was significant and correlated to yield patterns. There was as high as four-fold difference between available water content between coarse-textured and fine-textured soils on the study site. A good agreement was observed (RMSE = 0.052 cm3 cm-3 [cubic centimeter per cubic centimeter] and r = 0.88) between predicted and observed water contents. ECa and space images were useful proximal data to investigate soil spatial variability. The site-specific water production functions performed well at predicting cotton lint yield with RMSE equal to 0.131 Mg ha-1 [megagram per hectare] and 0.194 Mg ha-1 in 2013 and 2014, respectively. The findings revealed that variable rate irrigation with pie shape zones could enhance cotton lint yield under supplemental irrigation in west Tennessee
El papel de la enseñanza de matemáticas basada en problemas de acuerdo con el modelo de Kirkpatrick sobre el desempeño de resolución de problemas de los profesores de matemáticas
The process of evaluation is essentially the process of determining the realization of the educational
goals in real terms through curriculum and education and represents the changes that occur in human behavior.
Therefore, it is necessary that at the end of each training course (such as training classes, workshops, and
training seminars), the teacher or evaluators, evaluate the implemented training program. In the curriculum
approaches, learning the problem-solving ability is the ultimate goal of mathematics education. This skill requires
empowering teachers with problem solving skills as one of the optimal ways to use capacities and to achieve
educational goals. Therefore, the main goal of this study was to examine the problem-based mathematics
teaching according to the Krikpatrick's model on problem-solving performance of mathematics teachers. The
research design was of a pretest-posttest type with a control group. Using simple random sampling method, 100
male and female mathematics teachers, teaching mathematics at the middle school, were selected from Rabat
Karim city, Tehran province. In pre-test and post-test of the traditional teaching and problem-solving based
teaching in mathematics, data were collected through mathematical problem-solving performance test and
Kirkpatrick's four-level questionnaire. Using SPSS software and R software, the results showed a significant
difference between the scores of problem-solving performances between the two groups of control and
experiment after the training, and through the equations, we showed that each level of the Kirkpatrick's model
has a positive effect on the post-test scores of mathematics teachers.El proceso de evaluación es esencialmente el proceso de determinar la realización de los objetivos
educativos en términos reales a través del currÃculo y la educación, y representa los cambios que ocurren en el
comportamiento humano. Por lo tanto, es necesario que al final de cada curso de capacitación (como clases de
capacitación, talleres y seminarios de capacitación), el maestro o evaluadores evalúen el programa de
capacitación implementado. En los enfoques curriculares, aprender la capacidad de resolución de problemas es
el objetivo final de la educación matemática. Esta habilidad requiere empoderar a los maestros con habilidades
de resolución de problemas como una de las formas óptimas para usar las capacidades y alcanzar metas
educativas. Por lo tanto, el objetivo principal de este estudio fue examinar la enseñanza de las matemáticas
basada en problemas de acuerdo con el modelo de Krikpatrick sobre el rendimiento en la resolución de
problemas de los profesores de matemáticas. El diseño de la investigación fue de un tipo de prueba previa y
posterior con un grupo de control. Usando un método de muestreo aleatorio simple, se seleccionaron 100
maestros de matemáticas masculinos y femeninos, que enseñan matemáticas en la escuela secundaria, de la
ciudad de Rabat Karim, provincia de Teherán. En las pruebas previas y posteriores de la enseñanza tradicional
basada en la enseñanza de la resolución de problemas en matemáticas, los datos se recopilaron mediante la
prueba de rendimiento de la resolución de problemas matemáticos y el cuestionario de cuatro niveles de
Kirkpatrick. Usando el software SPSS y el software R, los resultados mostraron una diferencia significativa entre
los puntajes de desempeño de resolución de problemas entre los dos grupos de control y experimento después
del entrenamiento, y a través de las ecuaciones, demostramos que cada nivel del modelo de Kirkpatrick tiene un
efecto positivo en las puntuaciones posteriores a la prueba de los profesores de matemáticas
The examining two approaches for facilitating the process of arithmetic word problems solving
This paper focuses on two approaches for facilitating the process of word problems solving. The first approach distinguishes different kinds of occurred errors and the second one recognizes various required and underlying knowledge. The first approach applies Kinfong and Holtan's framework of occurred errors and the second approach applies Mayer’s theory (1992) of underlying knowledge for solving word problems. The main aim of this paper is to examine the relationship between different kinds of occurred errors and various required knowledge in solving Arithmetic word problems. The research methodology is a semi experimental method. The subjects include 89 eight grade students (male and female). The research tools are a descriptive math test regarding six word problems and a directed interview. The results indicate that in solving the arithmetic word problems, increasing students' errors result from lack of linguistic, semantic, structural and communicational knowledge. This study explored that the possible connection between the two approaches for facilitating solving word problems is very important. That is because clarity of this relationship may increase math teachers’ insight about the nature of different kinds of occurred errors and the different aspects of knowledge necessary for solving word problems
Estimating saturated hydraulic conductivity using different well known pedotransfer functions
Application of Fuzzy Neural Networks and Genetic Algorithm Neural Network in predicting water retention
Adjustments to the reference dataset design improve cell type label transfer
The transfer of cell type labels from pre-annotated (reference) to newly collected data is an important task in single-cell data analysis. As the number of publicly available annotated datasets which can be used as reference, as well as the number of computational methods for cell type label transfer are constantly growing, rationals to understand and decide which reference design and which method to use for a particular query dataset are needed. Using detailed data visualisations and interpretable statistical assessments, we benchmark a set of popular cell type annotation methods, test their performance on different cell types and study the effects of the design of reference data (e.g., cell sampling criteria, inclusion of multiple datasets in one reference, gene set selection) on the reliability of predictions. Our results highlight the need for further improvements in label transfer methods, as well as preparation of high-quality pre-annotated reference data of adequate sampling from all cell types of interest, for more reliable annotation of new datasets
Single-cell multi-omics and lineage tracing to dissect cell fate decision-making
The concept of cell fate relates to the future identity of a cell, and its daughters, which is obtained via cell differentiation and division. Understanding, predicting, and manipulating cell fate has been a long-sought goal of developmental and regenerative biology. Recent insights obtained from single-cell genomic and integrative lineage-tracing approaches have further aided to identify molecular features predictive of cell fate. In this perspective, we discuss these approaches with a focus on theoretical concepts and future directions of the field to dissect molecular mechanisms underlying cell fate
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