Developmental stages and important periods of probability cognition in 6 to 14 year-old students

This study chose 906 students of 6 to 14 years of age and focused on the developmental stages and important periods of probability cognition. The study shows that probability cognition of students aged 6-14 experiences the following 5 stages: slow development stage I (6-7 years old), quick development stage I (8-9 years old), slow development stage II (10 years old), quick development stage II (11-12 years old) and stagnant stage (13-14 years old). Additionally, there are two important periods in students’ cognitive development: 8-9 years old is the first period and 11-12 is the second. Even at the highest development stage, students can just understand the number representation, probability distribution and fraction representation while ca not reach the mastery level, which suggests the limitation of students’ probability cognition. Accordingly, curriculum should take students’ cognitive development level into account and set reasonable cognitive objectives

Avances de investigación en educación matemática

Resumen basado en el de la publicaciónResumen en español, portugués y francésSe presenta un estudio en el que se seleccionaron 906 estudiantes de 6 a 14 años de edad y se estudiaron las etapas de desarrollo y los períodos de cognición de la probabilidad. Se muestra que la cognición probabilística de los estudiantes de 6 a 14 años experimenta las siguientes 5 etapas: desarrollo lento I (6-7 años), desarrollo rápido I (8-9 años), desarrollo lento II (10 años), desarrollo rápido II (11-12 años) y fase consolidada (13-14 años). Además hay dos períodos importantes en el desarrollo cognitivo de los estudiantes: el primero a los 8-9 años de edad y el segundo a los 11-12. Incluso en la etapa de desarrollo más alta, los estudiantes pueden entender la representación numérica, la distribución de probabilidad y la representación fraccional, mientras que no pueden alcanzar el nivel de maestría, lo que sugiere la limitación de la cognición de los estudiantes. En consecuencia, el plan de estudios debe tener en cuenta el nivel de desarrollo cognitivo de los estudiantes y establecer objetivos cognitivos razonablesES

Effect of non-thermal effects in microwave heating on the rheology and chemical properties of petroleum asphalt

This study systematically analyses the rheological properties of typical petroleum asphalt heated by microwaves at different temperatures through viscosity, penetration, dynamic shear, low-temperature bending, and other rheological tests. The results show that the non-thermal effect of microwaves enhances the fluidity of petroleum asphalt in the high-temperature viscous flow state, becomes softer in the medium-temperature viscoelastic state, and becomes hard and brittle in the low-temperature glassy state. The effect of microwaves also causes some specific changes in the properties of bitumen, including softening point and glass transition temperature in the opposite direction, as well as a large difference in the response of bitumen of different viscosities. The chemical changes in microwave-heated bitumen were analyzed using component tests and microscopic observation. It was found that microwave heating homogenized and dispersed the asphaltene aggregates into small particles, with the heavy components significantly reduced and the light components increased

Experimental Investigation of the Performance of Corn Straw Fiber Cement-Stabilized Macadam

Recently, the application of plant fibers to improve the cementitious mix performance has attracted interest in the field of road materials owing to advantages of environmental protection and cost-effectiveness. As a planting crop, corn exhibits the advantages of being a more abundant resource with a wider distribution than those of other plant fibers. In this study, the effect of corn straw fiber on the properties of cement-stabilized macadam (5% cement) was investigated with the fiber length and content as variables. The test results revealed that the addition of a small amount of fiber marginally affects the compression density of cement-stabilized macadam. At a fiber length of 10 mm and a fiber content of 1%, the maximum increase in the compressive strength was 18.8%, and the maximum increase in the splitting strength was 35.4%. Moreover, at a fiber length of 15 mm and a fiber content of 1%, the shrinkage coefficient was reduced by 29%, and the crack resistance of cement-stabilized macadam was enhanced. In addition, the dry–wet cycle durability of cement-stabilized macadam was improved

An Object-Oriented Method for Extracting Single-Object Aquaculture Ponds from 10 m Resolution Sentinel-2 Images on Google Earth Engine

Aquaculture plays a key role in achieving Sustainable Development Goals (SDGs), while it is difficult to accurately extract single-object aquaculture ponds (SOAPs) from medium-resolution remote sensing images (Mr-RSIs). Due to the limited spatial resolutions of Mr-RSIs, most studies have aimed to obtain aquaculture areas rather than SOAPs. This study proposed an object-oriented method for extracting SOAPs. We developed an iterative algorithm combining grayscale morphology and edge detection to segment water bodies and proposed a segmentation degree detection approach to select and edit potential SOAPs. Then a classification decision tree combining aquaculture knowledge about morphological, spectral, and spatial characteristics of SOAPs was constructed for object filter. We selected a 707.26 km2 study region in Sri Lanka and realized our method on Google Earth Engine (GEE). A 25.11 km2 plot was chosen for verification, where 433 SOAPs were manually labeled from 0.5 m high-resolution RSIs. The results showed that our method could extract SOAPs with high accuracy. The relative error of total areas between extracted result and the labeled dataset was 1.13%. The MIoU of the proposed method was 0.6965, representing an improvement of between 0.1925 and 0.3268 over the comparative segmentation algorithms provided by GEE. The proposed method provides an available solution for extracting SOAPs over a large region and shows high spatiotemporal transferability and potential for identifying other objects

An Earth Observation Framework in Service of the Sendai Framework for Disaster Risk Reduction 2015–2030

The Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) proposed seven targets comprising 38 quantified indicators and various sub-indicators to monitor the progress of disaster risk and loss reduction efforts. However, challenges persist regarding the availability of disaster-related data and the required resources to address data gaps. A promising way to address this issue is the utilization of Earth observation (EO). In this study, we proposed an EO-based disaster evaluation framework in service of the SFDRR and applied it to the context of tropical cyclones (TCs). We first investigated the potential of EO in supporting the SFDRR indicators, and we then decoupled those EO-supported indicators into essential variables (EVs) based on regional disaster system theory (RDST) and the TC disaster chain. We established a mapping relationship between the measurement requirements of EVs and the capabilities of EO on Google Earth Engine (GEE). An end-to-end framework that utilizes EO to evaluate the SFDRR indicators was finally established. The results showed that the SFDRR contains 75 indicators, among which 18.7% and 20.0% of those indicators can be directly and indirectly supported by EO, respectively, indicating the significant role of EO for the SFDRR. We provided four EV classes with nine EVs derived from the EO-supported indicators in the proposed framework, along with available EO data and methods. Our proposed framework demonstrates that EO has an important contribution to supporting the implementation of the SFDRR, and that it provides effective evaluation solutions