A circumpolar perspective on fluvial sediment flux to the Arctic ocean

Quantification of sediment fluxes from rivers is fundamental to understanding land‐ocean linkages in the Arctic. Numerous publications have focused on this subject over the past century, yet assessments of temporal trends are scarce and consensus on contemporary fluxes is lacking. Published estimates vary widely, but often provide little accessory information needed to interpret the differences. We present a pan‐arctic synthesis of sediment flux from 19 arctic rivers, primarily focusing on contributions from the eight largest ones. For this synthesis, historical records and recent unpublished data were compiled from Russian, Canadian, and United States sources. Evaluation of these data revealed no long‐term trends in sediment flux, but did show stepwise changes in the historical records of two of the rivers. In some cases, old values that do not reflect contemporary fluxes are still being reported, while in other cases, typographical errors have been propagated into the recent literature. Most of the discrepancy among published estimates, however, can be explained by differences in years of records examined and gauging stations used. Variations in sediment flux from year to year in arctic rivers are large, so estimates based on relatively few years can differ substantially. To determine best contemporary estimates of sediment flux for the eight largest arctic rivers, we used a combination of newly available data, historical records, and literature values. These estimates contribute to our understanding of carbon, nutrient, and contaminant transport to the Arctic Ocean and provide a baseline for detecting future anthropogenic or natural change in the Arctic

A Talk on the Wild Side: The Direct and Indirect Impact of Speech Recognition on Learning Gains

Research in the learning sciences and mathematics education has suggested that ‘thinking aloud’ (verbalization) can be important for learning. In a technology-mediated learning environment, speech might also help to promote learning by enabling the system to infer the students’ cognitive and affective state so that they can be provided a sequence of tasks and formative feedback, both of which are adapted to their needs. For these and associated reasons, we developed the iTalk2Learn platform that includes speech production and speech recognition for children learning about fractions. We investigated the impact of iTalk2Learn’s speech functionality in classrooms in the UK and Germany, with our results indicating that a speech-enabled learning environment has the potential to enhance student learning gains and engagement, both directly and indirectly

Magnetic resonance imaging (MRI) of heavy-metal transport and fate in an artificial biofilm

Unlike planktonic systems, reaction rates in biofilms are often limited by mass transport, which controls the rate of supply of contaminants into the biofilm matrix. To help understand this phenomenon, we investigated the potential of magnetic resonance imaging (MRI) to spatially quantify copper transport and fate in biofilms. For this initial study we utilized an artificial biofilm composed of a 50:50 mix of bacteria and agar. MRI successfully mapped Cu2+ uptake into the artificial biofilm by mapping T2 relaxation rates. A calibration protocol was used to convert T2 values into actual copper concentrations. Immobilization rates in the artificial biofilm were slow compared to the rapid equilibration of planktonic systems. Even after 36 h, the copper front had migrated only 3 mm into the artificial biofilm and at this distance from the copper source, concentrations were very low. This slow equilibration is a result of (1) the time it takes copper to diffuse over such distances and (2) the adsorption of copper onto cell surfaces, which further impedes copper diffusion. The success of this trial run indicates MRI could be used to quantitatively map heavy metal transport and immobilization in natural biofilms

30/20 GHz Technology at TRW

TRW is developing two types of 20 GHz solid state power amplifiers: 1) an extremely complex 30 GHz receive antenna with both fixed and scanning beams, and 2) the electrical power conditioners (EPC) for a dual mode 7.5 and 75 watt 20 GHz travelling wave tube (TWT). The solid state amplifiers are a GaAs FET unit with 7.5 watt output and an impatt diode amplifier with 20 watts output. The impatt unit uses a 12 diode combiner with a combining efficiency of 80%. The current breadboard unit provides 17.18 watts output in the injection locked mode. The antenna uses an 80.5 inch carbon filament reinforced plastic offset parabola to produce 0.3° beams. The feed is polarization diplexed. Both polarizations are utilized to provide fixed and scanning beam with the feed set interspersed to solve the feed crowding problem. The feed assembly and waveguide structure are being integrated. The reflector tooling is nearly complete

Experimental and numerical analyses of laminar boundary-layer flow stability over an aircraft fuselage forebody

Fuelled by a need to reduce viscous drag of airframes, significant advances have been made in the last decade to design lifting surface geometries with considerable amounts of laminar flow. In contrast to the present understanding of practical limits for natural laminar flow over lifting surfaces, limited experimental results are available examining applicability of natural laminar flow over axisymmetric and nonaxisymmetric fuselage shapes at relevantly high length Reynolds numbers. The drag benefits attainable by realizing laminar flow over nonlifting aircraft components such as fuselages and nacelles are shown. A flight experiment to investigate transition location and transition mode over the forward fuselage of a light twin engine propeller driven airplane is examined

The GSFC scientific data storage problem

Scientific data storage problems of telemetry tape

Jamming transitions in a schematic model of suspension rheology

We study the steady-state response to applied stress in a simple scalar model of sheared colloids. Our model is based on a schematic (F2) model of the glass transition, with a memory term that depends on both stress and shear rate. For suitable parameters, we find transitions from a fluid to a nonergodic, jammed state, showing zero flow rate in an interval of applied stress. Although the jammed state is a glass, we predict that jamming transitions have an analytical structure distinct from that of the conventional mode coupling glass transition. The static jamming transition we discuss is also distinct from hydrodynamic shear thickening.Comment: 7 pages; 3 figures; improved version with added references. Accepted for publication in Europhysics Letter

Serrated trailing edges for improving lift and drag characteristics of lifting surfaces

An improvement in the lift and drag characteristics of a lifting surface is achieved by attaching a serrated panel to the trailing edge of the lifting surface. The serrations may have a saw-tooth configuration, with a 60 degree included angle between adjacent serrations. The serrations may vary in shape and size over the span-wise length of the lifting surface, and may be positioned at fixed or adjustable deflections relative to the chord of the lifting surface

Don’t Do Evil: Implementing Artificial Intelligence in Universities

Artificial Intelligence (AI) is changing the ways in which we experience everyday tasks, and its reach is extending into education. Promises of AI-driven personalised learning, learner agency, adaptive teaching and changes to teacher roles are increasingly becoming realistic but the ethical considerations surrounding these, and even simpler innovations are far from clear. Various ethical standards are proposed for AI, though these tend to be high-level and generic and do not serve to guide education practice. The multiple agencies concerned with AI analytics are also yet to provide a strong sense of direction. The Open University UK has established an AI working group to explore the contribution AI might make to improving student retention, success and satisfaction. With a specific emphasis on Artificial Intelligence in Education (AIEd), this paper proposes eight principles constituting an open ethical framework for implementing AI in educational settings in ways that empower students and provide transparency