Pursuant to recommendations by the National Academies of Science, Engineering and Medicine's Earth Science Decadal Survey [1], the National Aeronautics and Space Administration (NASA) has announced the development of an Earth System Observatory (ESO), a series of missions designed to observe processes across the Earth's interior, surface and atmosphere. A key component of this system is the Surface Biology and Geology (SBG) investigation. SBG will measure the composition and properties of Earth's land, inland waters, and coastal oceans. The notional architecture consists of multiple spacecraft slated for launch in the 2027–2028 timeframe (Figure 1). Target science questions and geophysical variables span diverse disciplines including terrestrial and aquatic ecology, geology, vulcanology, hydrology and cryospheric sciences (Figure 2). Beyond simply measuring geophysical variables for each discipline, SBG will provide information about the links between the different domains, enabling a more comprehensive understanding of the Earth as a connected system. SBG measurements will also benefit a wide range of societal applications including agriculture, terrestrial and aquatic biodiversity, natural hazards, public health, and management of water and other natural resources [2]. SBG will also coordinate measurements, data products, and analyses with other ESO elements to deliver an integrated Earth System perspective of Earth and its changing climate.

Beginning from the assumption that young children (ages 6-8) are capable of reasoning about complex phenomena [12], we set out to better understand dimensions of the Science through Technology Enhanced Play environment that provided support for children to learn about relationships between multiple levels of an emergent phenomenon [23] states of matter. We conducted interactional analysis [15] of several moments in two classrooms as students developed and refined understanding of rules that connect micro behavior of particles of water to macro understanding about states of matter. We argue that central to students' disciplinary work were (1) multiple forms of agency negotiated within the STEP environment that were deeply intertwined with (2) students' embodiment. Agency and embodiment both supported students' consensus understanding of relationships between levels of the states of matter phenomenon (3) through students' joyful and playful collaborative work. We examine several episodes in detail to explore these findings.

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission was selected as a NASA Earth-Ventures Instrument (EV-I) Class-D mission on the International Space Station (ISS) to be launched in April 2018. ECOSTRESS will answer science questions related to water use and availability in several key biomes of the terrestrial biosphere using surface temperature information measured from the thermal infrared (TIR) measurement. The instrument includes a TIR multispectral scanner with five spectral bands in the TIR between 8 and 12.5 μm and a spatial resolution of 60m. Model-derived evapotranspiration information derived from ECOSTRESS will help reveal how ecosystems change with climate and provide a critical link between the water cycle and plant health, both natural and agricultural. The inclined, precessing ISS orbit will also enable ECOSTRESS to sample the diurnal cycle in critical regions across the globe at spatiotemporal scales unexploited by current instruments in Sun-synchronous polar and high-altitude geostationary orbits. In this paper we will discuss the primary science objectives of ECOSTRESS, details of the Level 2, 3, and 4 science products and their derivation, validation strategies, and community outreach efforts.

There is a pressing need to globally inventory and assess coastal and inland aquatic habitats; extremely valuable and productive regions that are vulnerable to global anthropogenic pressures and climatic change. Basic information about sessile communities (wetlands, coral reefs, and sea grasses) includes mapping their extent and distribution, which can be gleaned from spectral surface reflectance imagery at high spatial resolution, but moderate temporal resolution. Moderate to high temporal resolution is also required for detailed observations of sessile community change (e.g., phenology, disturbance) and high temporal resolution is required for environmental changes in the surrounding water, phytoplankton concentration and composition, and concentrations of sediment or chromophoric dissolved organic matter (CDOM). Current and upcoming satellite missions and technology could meet spatial and spectral challenges. Multiple orbiting and airborne platforms, along with a network of in situ measurements, could provide a more complete picture of how these vital resources are changing. This paper provides an overview of these resources.

Work place engineering problems are recognized as being complex and ambiguous. However, most of the problems students are asked to solve during their degree programs are classroom problems. Most studies of ambiguity in problem solving have defined ambiguity as a characteristic of the problems. We are interested in understanding how students interpret engineering problems, either creating or resolving ambiguity during their problem solving process. The research question that guides this study is: How is ambiguity manifested by engineering students as they solve problems? This study is part of a larger project examining engineering students' engineering problem solving across different types of engineering problems. Twenty materials engineering students were asked to solve four materials engineering problems during a think-aloud session. For the analysis, points of ambiguity during the problem-solving process were identified as periods in which the students specifically verbalized uncertainty. The points of ambiguity in the transcript were then analyzed through script analysis. More specifically textual instances of ambiguity were linked with three main periods and situational categories: a) the situation that caused the ambiguity, 2) what happened during the point of ambiguity, and 3) the reaction of the student after reaching the point of ambiguity. Results indicated that students experienced points of ambiguity in both closed- and open-ended problems. Several motifs were common to both types of problems, including confusion over how to use given values, not having necessary content knowledge, lack of self-confidence, and difficulty conceptualizing the problem. The lack of constraints inherent in the open-ended problems also caused additional ambiguity among some students. Our findings show that ambiguity can take many forms and is not just a function of the problem structure. Students reach points of ambiguity (e.g., points where they do not know what to do next), due to many factors. Some of these factors represent aspects of their academic and epistemological development. Our analysis to date suggests that students need more comprehensive training and practice to be prepared in facing problems that reflect the work in engineering practice. We are currently examining the data further to identify patterns in their response to ambiguity, which may help in developing pedagogical strategies and tools to support students' ability to successfully solve engineering problems.

Open-ended problem solving is a skill that is central to engineering practice. As a consequence, developing skills in solving such problems is imperative for engineering graduates. Open-ended problems are often ill-defined and can have more than one viable solution. This paper presents preliminary results from a mixed methods study examining the specific problem solving strategies of undergraduate engineering students when dealing with the ambiguity of open-ended problems. Participants completed measures of content knowledge, epistemic beliefs, and working memory, and also solved four complex engineering problems during individual problem solving sessions. A subset of participants solved these problems during a think aloud session and participated in follow-up interviews. Preliminary analysis of quantitative data has focused on identifying correlations between problem solving solution scores and the measures of epistemic beliefs and working memory capacity. Analysis of qualitative data is examining the problem-solving processes students.

MOTIVATION: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. RESULTS: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. AVAILABILITY: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel) and Sun Solaris (SPARC), as well as the full source code under an open source license from http://www.copasi.org.