3,282 research outputs found
Experimental observation of nanoscale radiative heat flow due to surface plasmons in graphene and doped silicon
Owing to its two dimensional electronic structure, graphene exhibits many
unique properties. One of them is a wave vector and temperature dependent
plasmon in the infrared range. Theory predicts that due to these plasmons,
graphene can be used as a universal material to enhance nanoscale radiative
heat exchange for any dielectric substrate. Here we report on radiative heat
transfer experiments between SiC and a SiO2 sphere which have non matching
phonon polariton frequencies, and thus only weakly exchange heat in near field.
We observed that the heat flux contribution of graphene epitaxially grown on
SiC dominates at short distances. The influence of plasmons on radiative heat
transfer is further supported with measurements for doped silicon. These
results highlight graphenes strong potential in photonic nearfield and energy
conversion devices.Comment: 4 pages, 3 figure
Tuning the electron-phonon coupling in multilayer graphene with magnetic fields
Magneto Raman scattering study of the E optical phonons in multi-layer
epitaxial graphene grown on a carbon face of SiC are presented. At 4.2K in
magnetic field up to 33 T, we observe a series of well pronounced avoided
crossings each time the optically active inter Landau level transition is tuned
in resonance with the E phonon excitation (at 196 meV). The width of the
phonon Raman scattering response also shows pronounced variations and is
enhanced in conditions of resonance. The experimental results are well
reproduced by a model that gives directly the strength of the electron-phonon
interaction.Comment: 4 pages, 3 figure
Nutritional Status Assessment (SMO 016E)
The Nutritional Status Assessment Supplemental Medical Objective was initiated to expand nominal clinical nutrition testing of ISS astronauts, and to gain a better understanding of the time course of changes in nutritional status during flight. The primary activity of this effort was collecting blood and urine samples during flight for analysis after return to Earth. Samples were subjected to a battery of tests. The resulting data provide a comprehensive survey of how nutritional status and related systems are affected by 4-6 months of space flight. Analysis of these data has yielded many findings to date, including: Vision. Documented evidence that biochemical markers involved in one-carbon metabolism were altered in crewmembers who experienced vision-related issues during and after flight (1). Iron, Oxidative Stress, and Bone. In-flight data document a clear association of increased iron stores, markers of oxidative damage to DNA, and bone loss (2). Exercise. Documented that well-nourished crewmembers performing heavy resistance exercise returned from ISS with bone mineral densities unchanged from preflight (3). Furthermore, the response of bone to space flight and exercise countermeasures was the same in men and women (4). Body Mass. Crewmembers lose 2-5% of their body mass in the first month of flight, and maintain the lower body mass during flight (5). Additionally, the two devices to measure body mass on orbit, the SLAMMD and BMMD, provide similar results (5). Cytokines. Findings indicated that a pattern of persistent physiological adaptations occurs during space flight that includes shifts in immune and hormonal regulation (6). Fish/Bone. Documented a relationship between fish intake and bone loss in astronauts (that is, those who ate more fish lost less bone) (7). Vitamin K. Documented that in generally well-fed and otherwise healthy individuals, vitamin K status and bone vitamin K-dependent proteins are unaffected by space flight (and bed rest) (8). Testosterone. Documented that blood concentrations of testosterone were unchanged during flight, but a transient decline occurred after landing (9). Calcium. Nutrition SMO data contributed to the ISS Program by helping understand how and why the Urine Processor Assembly clogged with calcium sulfate precipitate (10). Sample Processing. Ground-based analytical testing results have also been published (11)
Prior knowledge about events depicted in scenes decreases oculomotor exploration.
The visual input that the eyes receive usually contains temporally continuous information about unfolding events. Therefore, humans can accumulate knowledge about their current environment. Typical studies on scene perception, however, involve presenting multiple unrelated images and thereby render this accumulation unnecessary. Our study, instead, facilitated it and explored its effects. Specifically, we investigated how recently-accumulated prior knowledge affects gaze behavior. Participants viewed sequences of static film frames that contained several 'context frames' followed by a 'critical frame'. The context frames showed either events from which the situation depicted in the critical frame naturally followed, or events unrelated to this situation. Therefore, participants viewed identical critical frames while possessing prior knowledge that was either relevant or irrelevant to the frames' content. In the former case, participants' gaze behavior was slightly more exploratory, as revealed by seven gaze characteristics we analyzed. This result demonstrates that recently-gained prior knowledge reduces exploratory eye movements
Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models.
Human visual experience usually provides ample opportunity to accumulate knowledge about events unfolding in the environment. In typical scene perception experiments, however, participants view images that are unrelated to each other and, therefore, they cannot accumulate knowledge relevant to the upcoming visual input. Consequently, the influence of such knowledge on how this input is processed remains underexplored. Here, we investigated this influence in the context of gaze control. We used sequences of static film frames arranged in a way that allowed us to compare eye movements to identical frames between two groups: a group that accumulated prior knowledge relevant to the situations depicted in these frames and a group that did not. We used a machine learning approach based on hidden Markov models fitted to individual scanpaths to demonstrate that the gaze patterns from the two groups differed systematically and, thereby, showed that recently accumulated prior knowledge contributes to gaze control. Next, we leveraged the interpretability of hidden Markov models to characterize these differences. Additionally, we report two unexpected and interesting caveats of our approach. Overall, our results highlight the importance of recently acquired prior knowledge for oculomotor control and the potential of hidden Markov models as a tool for investigating it
Nutritional Status Assessment (SMO -16E)
The Nutritional Status Assessment Supplemental Medical Objective was an experiment initiated to expand nominal pre- and postflight clinical nutrition testing, and to gain a better understanding of the time course of changes during flight. The primary activity of this effort was collecting blood and urine samples 5 times during flight for analysis after return to Earth. Samples were subjected to a battery of tests, including nutritional, physiological, general chemistry, and endocrinology indices. These data provide a comprehensive survey of how nutritional status and related systems are affected by 4-6 months of space flight. Analyzing the data will help us to define nutritional requirements for long-duration missions, and better understand human adaptation to microgravity. This expanded set of measurements will also aid in the identification of nutritional countermeasures to counteract, for example, the deleterious effects of microgravity on bone and muscle and the effects of space radiation
Machine learning and robust MPC for frequency regulation with heat pumps
With the increased amount of volatile renewable energy sources connected to
the electricity grid, there is an increased need for frequency regulation. On
the demand side, frequency regulation services can be offered by buildings that
are equipped with electric heating or cooling systems, by exploiting the
thermal inertia of the building. Existing approaches for tapping into this
potential typically rely on a first-principles building model, which in
practice can be expensive to obtain and maintain. Here, we use the thermal
inertia of a buffer storage instead, reducing the model of the building to a
demand forecast. By combining a control scheme based on robust Model Predictive
Control, with heating demand forecasting based on Artificial Neural Networks
and online correction methods, we offer frequency regulation reserves and
maintain user comfort with a system comprising a heat pump and a storage tank.
We improve the exploitation of the small thermal capacity of buffer storage by
using affine policies on uncertain variables. These are chosen optimally in
advance, and modify the planned control sequence as the values of uncertain
variables are discovered. In a three day experiment with a real multi-use
building we show that the scheme is able to offer reserves and track a
regulation signal while meeting the heating demand of the building. In
additional numerical studies, we demonstrate that using affine policies
significantly decreases the cost function and increases the amount of offered
reserves and we investigate the suboptimality in comparison to an omniscient
control system.Comment: 13 pages, 12 figures, 1 table, submitted to IEEE Transactions on
Control Systems Technolog
Multi-shell gold nanowires under compression
Deformation properties of multi-wall gold nanowires under compressive loading
are studied. Nanowires are simulated using a realistic many-body potential.
Simulations start from cylindrical fcc(111) structures at T=0 K. After
annealing cycles axial compression is applied on multi-shell nanowires for a
number of radii and lengths at T=300 K. Several types of deformation are found,
such as large buckling distortions and progressive crushing. Compressed
nanowires are found to recover their initial lengths and radii even after
severe structural deformations. However, in contrast to carbon nanotubes
irreversible local atomic rearrangements occur even under small compressions.Comment: 1 gif figure, 5 ps figure
ScatterShot: Interactive In-context Example Curation for Text Transformation
The in-context learning capabilities of LLMs like GPT-3 allow annotators to
customize an LLM to their specific tasks with a small number of examples.
However, users tend to include only the most obvious patterns when crafting
examples, resulting in underspecified in-context functions that fall short on
unseen cases. Further, it is hard to know when "enough" examples have been
included even for known patterns. In this work, we present ScatterShot, an
interactive system for building high-quality demonstration sets for in-context
learning. ScatterShot iteratively slices unlabeled data into task-specific
patterns, samples informative inputs from underexplored or not-yet-saturated
slices in an active learning manner, and helps users label more efficiently
with the help of an LLM and the current example set. In simulation studies on
two text perturbation scenarios, ScatterShot sampling improves the resulting
few-shot functions by 4-5 percentage points over random sampling, with less
variance as more examples are added. In a user study, ScatterShot greatly helps
users in covering different patterns in the input space and labeling in-context
examples more efficiently, resulting in better in-context learning and less
user effort.Comment: IUI 2023: 28th International Conference on Intelligent User
Interface
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