How Fault Surface Features Can Tell Us About Future Earthquakes

A new study suggests ways to quantify fault maturity, a property that affects earthquake characteristics.

Permafrost Dynamics and Degradation in Polar Arctic From Satellite Radar Observations, Yamal Peninsula

We investigate permafrost surface features revealed from satellite radar data in the Siberian arctic at the Yamal peninsula. Surface dynamics analysis based on SRTM and TanDEM-X DEMs shows up to 2 m net loss of surface relief between 2000 and 2014 indicating a highly dynamic landscape. Surface features for the past 14 years reflect an increase in small stream channels and a number of new lakes that developed, likely caused by permafrost thaw. We used Sentinel-1 SAR imagery to measure permafrost surface changes. Owing to limited observation data we analyzed only 2 years. The InSAR time-series has detected surface displacements in three distinct spatial locations during 2017 and 2018. At these three locations, 60–120 mm/yr rates of seasonal surface permafrost changes are observed. Spatial location of seasonal ground displacements aligns well with lithology. One of them is located on marine sediments and is linked to anthropogenic impact on permafrost stability. Two other areas are located within alluvial sediments and are at the top of topographic elevated zones. We discuss the influence of the geologic environment and the potential effect of local upwelling of gas. These combined analyses of InSAR time-series with analysis of geomorphic features from DEMs present an important tool for continuous process monitoring of surface dynamics as part of a global warming risk assessment.

Numeracy equipment and Year 3 children : "bright, shiny stuff" or supporting the development of part-whole thinking?

New Zealand teachers' use of equipment has increased as a result of their participation in the Numeracy Development Project. The purpose of this study was to discover how closely the children's reasons for their equipment choices matched their teachers' reasons for including the same pieces of equipment in their numeracy programmes. In the teachers' reasons for equipment choices, the surface features of equipment seemed equally important as the conceptual development the equipment can support. In contrast, the reasons given for equipment choices by the 34 Year 3 children who were interviewed were almost exclusively concerned with how the equipment might help them to solve the given problem. The children's success rates at solving the problem declined as the equipment became more structured; this paralleled the teachers' equipment choices. The equipment choices of the four teachers interviewed in this study were not strongly consistent with the equipment use recommended in the NDP materials.

Numeracy equipment and Year 3 children : "bright, shiny stuff" or supporting the development of part-whole thinking?

New Zealand teachers' use of equipment has increased as a result of their participation in the Numeracy Development Project. The purpose of this study was to discover how closely the children's reasons for their equipment choices matched their teachers' reasons for including the same pieces of equipment in their numeracy programmes. In the teachers' reasons for equipment choices, the surface features of equipment seemed equally important as the conceptual development the equipment can support. In contrast, the reasons given for equipment choices by the 34 Year 3 children who were interviewed were almost exclusively concerned with how the equipment might help them to solve the given problem. The children's success rates at solving the problem declined as the equipment became more structured; this paralleled the teachers' equipment choices. The equipment choices of the four teachers interviewed in this study were not strongly consistent with the equipment use recommended in the NDP materials.

Artificial Grammar Learning in Children With Developmental Language Disorder

Purpose: The purpose of the study was to evaluate implicit learning in children with developmental language disorder (DLD) by employing a visual artificial grammar learning task. Method: Thirteen children with DLD and 24 children with typical language development between the ages of 8 and 12 years completed a visual artificial grammar learning task. During the training phase of the task, participants were presented with strings of shapes that followed the underlying structure of a finite grammar. During the testing phase, participants were asked to judge whether new strings were grammatical or nongrammatical. Grammatical judgment of new strings served to measure generalization of the underlying grammatical structure. Endorsement based on chunk strength, or similarity to training exemplars, served to evaluate the extent to which children relied on surface features to guide their task performance. Results: As a group, children with typical development performed better on the artificial grammar learning task, compared with children with DLD, and accepted more grammatical strings regardless of their similarity to training exemplars. Task performance in both groups was not affected by surface features. Performance of children with DLD whose test accuracy exceeded the learning threshold of 0.5 was consistent with a generalization of the underlying grammatical structure that was unaffected by surface features. Conclusions: The study found group differences in learning outcomes between children with and without DLD. Consistent with previous reports, children with typical development correctly endorsed more grammatical strings than children with DLD, suggesting a better acquisition of the grammatical structure. However, there was no evidence to suggest that children in the DLD group (learners and nonlearners) relied on surface features (i.e., familiarity to training exemplars) in their grammatical judgment. These results refute our hypothesis that children in the DLD group would show judgment based on familiarity.

Analyzing Pixel-Level Relationships between Luojia 1-01 Nighttime Light and Urban Surface Features by Separating the Pixel Blooming Effect

Nighttime light (NTL) remote sensing data can effectively reveal human activities in urban development. It has received extensive attention in recent years, owing to its advantages in monitoring urban socio-economic activities. Due to the coarse spatial resolution and blooming effect, few studies can explain the factors influencing NTL variations at a fine scale. This study explores the relationships between Luojia 1-01 NTL intensity and urban surface features at the pixel level. The Spatial Durbin model is used to measure the contributions of different urban surface features (represented by Points-of-interest (POIs), roads, water body and vegetation) to NTL intensity. The contributions of different urban surface features to NTL intensity and the Pixel Blooming Effect (PIBE) are effectively separated by direct effect and indirect effect (pseudo-R2 = 0.915; Pearson correlation = 0.774; Moran’s I = 0.014). The results show that the contributions of different urban surface features to NTL intensity and PIBE are significantly different. Roads and transportation facilities are major contributors to NTL intensity and PIBE. The contribution of commercial area is much lower than that of roads in terms of PIBE. The inhibitory effect of water body is weaker than that of vegetation in terms of NTL intensity and PIBE. For each urban surface feature, the direct contribution to NTL intensity is far less than the indirect contribution (PIBE of total neighbors), but greater than the marginal indirect effect (PIBE of each neighbor). The method proposed in this study is expected to provide a reference for explaining the composition and blooming effect of NTL, as well as the application of NTL data in the urban interior.